## Run Mcp Tool `mcp_servers.tools.run(strtool_id, ToolRunParams**kwargs) -> ToolExecutionResult` **post** `/v1/mcp-servers/{mcp_server_id}/tools/{tool_id}/run` Execute a specific MCP tool The request body should contain the tool arguments in the ToolExecuteRequest format. ### Parameters - `mcp_server_id: str` - `tool_id: str` - `args: Optional[Dict[str, object]]` Arguments to pass to the tool ### Returns - `class ToolExecutionResult: …` - `status: Literal["success", "error"]` The status of the tool execution and return object - `"success"` - `"error"` - `agent_state: Optional[AgentState]` Representation of an agent's state. This is the state of the agent at a given time, and is persisted in the DB backend. The state has all the information needed to recreate a persisted agent. - `id: str` The id of the agent. Assigned by the database. - `agent_type: AgentType` The type of agent. - `"memgpt_agent"` - `"memgpt_v2_agent"` - `"letta_v1_agent"` - `"react_agent"` - `"workflow_agent"` - `"split_thread_agent"` - `"sleeptime_agent"` - `"voice_convo_agent"` - `"voice_sleeptime_agent"` - `blocks: List[Block]` The memory blocks used by the agent. - `value: str` Value of the block. - `id: Optional[str]` The human-friendly ID of the Block - `base_template_id: Optional[str]` The base template id of the block. - `created_by_id: Optional[str]` The id of the user that made this Block. - `deployment_id: Optional[str]` The id of the deployment. - `description: Optional[str]` Description of the block. - `entity_id: Optional[str]` The id of the entity within the template. - `hidden: Optional[bool]` If set to True, the block will be hidden. - `is_template: Optional[bool]` Whether the block is a template (e.g. saved human/persona options). - `label: Optional[str]` Label of the block (e.g. 'human', 'persona') in the context window. - `last_updated_by_id: Optional[str]` The id of the user that last updated this Block. - `limit: Optional[int]` Character limit of the block. - `metadata: Optional[Dict[str, object]]` Metadata of the block. - `preserve_on_migration: Optional[bool]` Preserve the block on template migration. - `project_id: Optional[str]` The associated project id. - `read_only: Optional[bool]` Whether the agent has read-only access to the block. - `tags: Optional[List[str]]` The tags associated with the block. - `template_id: Optional[str]` The id of the template. - `template_name: Optional[str]` Name of the block if it is a template. - `llm_config: LlmConfig` Deprecated: Use `model` field instead. The LLM configuration used by the agent. - `context_window: int` The context window size for the model. - `model: str` LLM model name. - `model_endpoint_type: Literal["openai", "anthropic", "google_ai", 27 more]` The endpoint type for the model. - `"openai"` - `"anthropic"` - `"google_ai"` - `"google_vertex"` - `"azure"` - `"groq"` - `"ollama"` - `"webui"` - `"webui-legacy"` - `"lmstudio"` - `"lmstudio-legacy"` - `"lmstudio-chatcompletions"` - `"llamacpp"` - `"koboldcpp"` - `"vllm"` - `"hugging-face"` - `"minimax"` - `"moonshot"` - `"moonshot_coding"` - `"mistral"` - `"together"` - `"bedrock"` - `"deepseek"` - `"xai"` - `"zai"` - `"zai_coding"` - `"baseten"` - `"fireworks"` - `"openrouter"` - `"chatgpt_oauth"` - `compatibility_type: Optional[Literal["gguf", "mlx"]]` The framework compatibility type for the model. - `"gguf"` - `"mlx"` - `display_name: Optional[str]` A human-friendly display name for the model. - `effort: Optional[Literal["low", "medium", "high", 2 more]]` The effort level for Anthropic models that support it (Opus 4.5+). Controls token spending and thinking behavior. Not setting this gives similar performance to 'high'. - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `"max"` - `enable_reasoner: Optional[bool]` Whether or not the model should use extended thinking if it is a 'reasoning' style model - `frequency_penalty: Optional[float]` Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. From OpenAI: Number between -2.0 and 2.0. - `handle: Optional[str]` The handle for this config, in the format provider/model-name. - `max_reasoning_tokens: Optional[int]` Configurable thinking budget for extended thinking. Used for enable_reasoner and also for Google Vertex models like Gemini 2.5 Flash. Minimum value is 1024 when used with enable_reasoner. - `max_tokens: Optional[int]` The maximum number of tokens to generate. If not set, the model will use its default value. - `model_endpoint: Optional[str]` The endpoint for the model. - `model_wrapper: Optional[str]` The wrapper for the model. - `parallel_tool_calls: Optional[bool]` Deprecated: Use model_settings to configure parallel tool calls instead. If set to True, enables parallel tool calling. Defaults to False. - `provider_category: Optional[ProviderCategory]` The provider category for the model. - `"base"` - `"byok"` - `provider_name: Optional[str]` The provider name for the model. - `put_inner_thoughts_in_kwargs: Optional[bool]` Puts 'inner_thoughts' as a kwarg in the function call if this is set to True. This helps with function calling performance and also the generation of inner thoughts. - `reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]` The reasoning effort to use when generating text reasoning models - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format: Optional[ResponseFormat]` The response format for the model's output. Supports text, json_object, and json_schema (structured outputs). Can be set via model_settings. - `class TextResponseFormat: …` Response format for plain text responses. - `type: Optional[Literal["text"]]` The type of the response format. - `"text"` - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `json_schema: Dict[str, object]` The JSON schema of the response. - `type: Optional[Literal["json_schema"]]` The type of the response format. - `"json_schema"` - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `type: Optional[Literal["json_object"]]` The type of the response format. - `"json_object"` - `return_logprobs: Optional[bool]` Whether to return log probabilities of the output tokens. Useful for RL training. - `return_token_ids: Optional[bool]` Whether to return token IDs for all LLM generations via SGLang native endpoint. Required for multi-turn RL training with loss masking. Only works with SGLang provider. - `strict: Optional[bool]` Enable strict mode for tool calling. When true, tool schemas include strict: true and additionalProperties: false, guaranteeing tool outputs match JSON schemas. - `temperature: Optional[float]` The temperature to use when generating text with the model. A higher temperature will result in more random text. - `tier: Optional[str]` The cost tier for the model (cloud only). - `tool_call_parser: Optional[str]` SGLang tool call parser name (e.g. 'glm47', 'qwen25', 'hermes'). Used by the SGLang native adapter to parse tool calls from raw model output. - `top_logprobs: Optional[int]` Number of most likely tokens to return at each position (0-20). Requires return_logprobs=True. - `verbosity: Optional[Literal["low", "medium", "high"]]` Soft control for how verbose model output should be, used for GPT-5 models. - `"low"` - `"medium"` - `"high"` - `memory: Memory` Deprecated: Use `blocks` field instead. The in-context memory of the agent. - `blocks: List[Block]` Memory blocks contained in the agent's in-context memory - `value: str` Value of the block. - `id: Optional[str]` The human-friendly ID of the Block - `base_template_id: Optional[str]` The base template id of the block. - `created_by_id: Optional[str]` The id of the user that made this Block. - `deployment_id: Optional[str]` The id of the deployment. - `description: Optional[str]` Description of the block. - `entity_id: Optional[str]` The id of the entity within the template. - `hidden: Optional[bool]` If set to True, the block will be hidden. - `is_template: Optional[bool]` Whether the block is a template (e.g. saved human/persona options). - `label: Optional[str]` Label of the block (e.g. 'human', 'persona') in the context window. - `last_updated_by_id: Optional[str]` The id of the user that last updated this Block. - `limit: Optional[int]` Character limit of the block. - `metadata: Optional[Dict[str, object]]` Metadata of the block. - `preserve_on_migration: Optional[bool]` Preserve the block on template migration. - `project_id: Optional[str]` The associated project id. - `read_only: Optional[bool]` Whether the agent has read-only access to the block. - `tags: Optional[List[str]]` The tags associated with the block. - `template_id: Optional[str]` The id of the template. - `template_name: Optional[str]` Name of the block if it is a template. - `agent_type: Optional[Union[AgentType, str, null]]` Agent type controlling prompt rendering. - `Literal["memgpt_agent", "memgpt_v2_agent", "letta_v1_agent", 6 more]` - `"memgpt_agent"` - `"memgpt_v2_agent"` - `"letta_v1_agent"` - `"react_agent"` - `"workflow_agent"` - `"split_thread_agent"` - `"sleeptime_agent"` - `"voice_convo_agent"` - `"voice_sleeptime_agent"` - `str` - `file_blocks: Optional[List[MemoryFileBlock]]` Special blocks representing the agent's in-context memory of an attached file - `file_id: str` Unique identifier of the file. - `is_open: bool` True if the agent currently has the file open. - `source_id: str` Deprecated: Use `folder_id` field instead. Unique identifier of the source. - `value: str` Value of the block. - `id: Optional[str]` The human-friendly ID of the Block - `base_template_id: Optional[str]` The base template id of the block. - `created_by_id: Optional[str]` The id of the user that made this Block. - `deployment_id: Optional[str]` The id of the deployment. - `description: Optional[str]` Description of the block. - `entity_id: Optional[str]` The id of the entity within the template. - `hidden: Optional[bool]` If set to True, the block will be hidden. - `is_template: Optional[bool]` Whether the block is a template (e.g. saved human/persona options). - `label: Optional[str]` Label of the block (e.g. 'human', 'persona') in the context window. - `last_accessed_at: Optional[datetime]` UTC timestamp of the agent’s most recent access to this file. Any operations from the open, close, or search tools will update this field. - `last_updated_by_id: Optional[str]` The id of the user that last updated this Block. - `limit: Optional[int]` Character limit of the block. - `metadata: Optional[Dict[str, object]]` Metadata of the block. - `preserve_on_migration: Optional[bool]` Preserve the block on template migration. - `project_id: Optional[str]` The associated project id. - `read_only: Optional[bool]` Whether the agent has read-only access to the block. - `tags: Optional[List[str]]` The tags associated with the block. - `template_id: Optional[str]` The id of the template. - `template_name: Optional[str]` Name of the block if it is a template. - `git_enabled: Optional[bool]` Whether this agent uses git-backed memory with structured labels. - `prompt_template: Optional[str]` Deprecated. Ignored for performance. - `name: str` The name of the agent. - `sources: List[Source]` Deprecated: Use `folders` field instead. The sources used by the agent. - `id: str` The human-friendly ID of the Source - `embedding_config: EmbeddingConfig` The embedding configuration used by the source. - `embedding_dim: int` The dimension of the embedding. - `embedding_endpoint_type: Literal["openai", "anthropic", "bedrock", 16 more]` The endpoint type for the model. - `"openai"` - `"anthropic"` - `"bedrock"` - `"google_ai"` - `"google_vertex"` - `"azure"` - `"groq"` - `"ollama"` - `"webui"` - `"webui-legacy"` - `"lmstudio"` - `"lmstudio-legacy"` - `"llamacpp"` - `"koboldcpp"` - `"vllm"` - `"hugging-face"` - `"mistral"` - `"together"` - `"pinecone"` - `embedding_model: str` The model for the embedding. - `azure_deployment: Optional[str]` The Azure deployment for the model. - `azure_endpoint: Optional[str]` The Azure endpoint for the model. - `azure_version: Optional[str]` The Azure version for the model. - `batch_size: Optional[int]` The maximum batch size for processing embeddings. - `embedding_chunk_size: Optional[int]` The chunk size of the embedding. - `embedding_endpoint: Optional[str]` The endpoint for the model (`None` if local). - `handle: Optional[str]` The handle for this config, in the format provider/model-name. - `name: str` The name of the source. - `created_at: Optional[datetime]` The timestamp when the source was created. - `created_by_id: Optional[str]` The id of the user that made this Tool. - `description: Optional[str]` The description of the source. - `instructions: Optional[str]` Instructions for how to use the source. - `last_updated_by_id: Optional[str]` The id of the user that made this Tool. - `metadata: Optional[Dict[str, object]]` Metadata associated with the source. - `updated_at: Optional[datetime]` The timestamp when the source was last updated. - `vector_db_provider: Optional[VectorDBProvider]` The vector database provider used for this source's passages - `"native"` - `"tpuf"` - `"pinecone"` - `system: str` The system prompt used by the agent. - `tags: List[str]` The tags associated with the agent. - `tools: List[Tool]` The tools used by the agent. - `id: str` The human-friendly ID of the Tool - `args_json_schema: Optional[Dict[str, object]]` The args JSON schema of the function. - `created_by_id: Optional[str]` The id of the user that made this Tool. - `default_requires_approval: Optional[bool]` Default value for whether or not executing this tool requires approval. - `description: Optional[str]` The description of the tool. - `enable_parallel_execution: Optional[bool]` If set to True, then this tool will potentially be executed concurrently with other tools. Default False. - `json_schema: Optional[Dict[str, object]]` The JSON schema of the function. - `last_updated_by_id: Optional[str]` The id of the user that made this Tool. - `metadata: Optional[Dict[str, object]]` A dictionary of additional metadata for the tool. - `name: Optional[str]` The name of the function. - `npm_requirements: Optional[List[NpmRequirement]]` Optional list of npm packages required by this tool. - `name: str` Name of the npm package. - `version: Optional[str]` Optional version of the package, following semantic versioning. - `pip_requirements: Optional[List[PipRequirement]]` Optional list of pip packages required by this tool. - `name: str` Name of the pip package. - `version: Optional[str]` Optional version of the package, following semantic versioning. - `project_id: Optional[str]` The project id of the tool. - `return_char_limit: Optional[int]` The maximum number of characters in the response. - `source_code: Optional[str]` The source code of the function. - `source_type: Optional[str]` The type of the source code. - `tags: Optional[List[str]]` Metadata tags. - `tool_type: Optional[ToolType]` The type of the tool. - `"custom"` - `"letta_core"` - `"letta_memory_core"` - `"letta_multi_agent_core"` - `"letta_sleeptime_core"` - `"letta_voice_sleeptime_core"` - `"letta_builtin"` - `"letta_files_core"` - `"external_langchain"` - `"external_composio"` - `"external_mcp"` - `base_template_id: Optional[str]` The base template id of the agent. - `compaction_settings: Optional[CompactionSettings]` Configuration for conversation compaction / summarization. Per-model settings (temperature, max tokens, etc.) are derived from the default configuration for that handle. - `clip_chars: Optional[int]` The maximum length of the summary in characters. If none, no clipping is performed. - `mode: Optional[Literal["all", "sliding_window", "self_compact_all", "self_compact_sliding_window"]]` The type of summarization technique use. - `"all"` - `"sliding_window"` - `"self_compact_all"` - `"self_compact_sliding_window"` - `model: Optional[str]` Model handle to use for sliding_window/all summarization (format: provider/model-name). If None, uses lightweight provider-specific defaults. - `model_settings: Optional[CompactionSettingsModelSettings]` Optional model settings used to override defaults for the summarizer model. - `class OpenAIModelSettings: …` - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["openai"]]` The type of the provider. - `"openai"` - `reasoning: Optional[Reasoning]` The reasoning configuration for the model. - `reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]` The reasoning effort to use when generating text reasoning models - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `strict: Optional[bool]` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature: Optional[float]` The temperature of the model. - `class CompactionSettingsModelSettingsSgLangModelSettings: …` SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["sglang"]]` The type of the provider. - `"sglang"` - `reasoning: Optional[CompactionSettingsModelSettingsSgLangModelSettingsReasoning]` The reasoning configuration for the model. - `reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]` The reasoning effort to use when generating text reasoning models - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format: Optional[CompactionSettingsModelSettingsSgLangModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `strict: Optional[bool]` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature: Optional[float]` The temperature of the model. - `tool_call_parser: Optional[str]` SGLang tool call parser name (for example 'glm47', 'qwen25', or 'hermes'). - `class AnthropicModelSettings: …` - `effort: Optional[Literal["low", "medium", "high", 2 more]]` Effort level for supported Anthropic models (controls token spending). 'xhigh' and 'max' are available on Opus 4.6+. Not setting this gives similar performance to 'high'. - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `"max"` - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["anthropic"]]` The type of the provider. - `"anthropic"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `strict: Optional[bool]` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature: Optional[float]` The temperature of the model. - `thinking: Optional[Thinking]` The thinking configuration for the model. - `budget_tokens: Optional[int]` The maximum number of tokens the model can use for extended thinking. - `type: Optional[Literal["enabled", "disabled"]]` The type of thinking to use. - `"enabled"` - `"disabled"` - `verbosity: Optional[Literal["low", "medium", "high"]]` Soft control for how verbose model output should be, used for GPT-5 models. - `"low"` - `"medium"` - `"high"` - `class GoogleAIModelSettings: …` - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["google_ai"]]` The type of the provider. - `"google_ai"` - `response_schema: Optional[ResponseSchema]` The response schema for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `temperature: Optional[float]` The temperature of the model. - `thinking_config: Optional[ThinkingConfig]` The thinking configuration for the model. - `include_thoughts: Optional[bool]` Whether to include thoughts in the model's response. - `thinking_budget: Optional[int]` The thinking budget for the model. - `class GoogleVertexModelSettings: …` - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["google_vertex"]]` The type of the provider. - `"google_vertex"` - `response_schema: Optional[ResponseSchema]` The response schema for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `temperature: Optional[float]` The temperature of the model. - `thinking_config: Optional[ThinkingConfig]` The thinking configuration for the model. - `include_thoughts: Optional[bool]` Whether to include thoughts in the model's response. - `thinking_budget: Optional[int]` The thinking budget for the model. - `class AzureModelSettings: …` Azure OpenAI model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["azure"]]` The type of the provider. - `"azure"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `temperature: Optional[float]` The temperature of the model. - `class XaiModelSettings: …` xAI model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["xai"]]` The type of the provider. - `"xai"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `temperature: Optional[float]` The temperature of the model. - `class CompactionSettingsModelSettingsMoonshotModelSettings: …` Moonshot/Kimi model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["moonshot"]]` The type of the provider. - `"moonshot"` - `response_format: Optional[CompactionSettingsModelSettingsMoonshotModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `strict: Optional[bool]` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature: Optional[float]` The temperature of the model. - `class CompactionSettingsModelSettingsZaiModelSettings: …` Z.ai (ZhipuAI) model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["zai"]]` The type of the provider. - `"zai"` - `response_format: Optional[CompactionSettingsModelSettingsZaiModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `temperature: Optional[float]` The temperature of the model. - `thinking: Optional[CompactionSettingsModelSettingsZaiModelSettingsThinking]` The thinking configuration for GLM-4.5+ models. - `clear_thinking: Optional[bool]` If False, preserved thinking is used (recommended for agents). - `type: Optional[Literal["enabled", "disabled"]]` Whether thinking is enabled or disabled. - `"enabled"` - `"disabled"` - `class CompactionSettingsModelSettingsMoonshotCodingModelSettings: …` Kimi Code model configuration (Anthropic-compatible). - `effort: Optional[Literal["low", "medium", "high", 2 more]]` Effort level for supported Anthropic models (controls token spending). 'xhigh' and 'max' are available on Opus 4.6+. Not setting this gives similar performance to 'high'. - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `"max"` - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["moonshot_coding"]]` The type of the provider. - `"moonshot_coding"` - `response_format: Optional[CompactionSettingsModelSettingsMoonshotCodingModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `strict: Optional[bool]` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature: Optional[float]` The temperature of the model. - `thinking: Optional[CompactionSettingsModelSettingsMoonshotCodingModelSettingsThinking]` The thinking configuration for the model. - `budget_tokens: Optional[int]` The maximum number of tokens the model can use for extended thinking. - `type: Optional[Literal["enabled", "disabled"]]` The type of thinking to use. - `"enabled"` - `"disabled"` - `verbosity: Optional[Literal["low", "medium", "high"]]` Soft control for how verbose model output should be, used for GPT-5 models. - `"low"` - `"medium"` - `"high"` - `class GroqModelSettings: …` Groq model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["groq"]]` The type of the provider. - `"groq"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `temperature: Optional[float]` The temperature of the model. - `class DeepseekModelSettings: …` Deepseek model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["deepseek"]]` The type of the provider. - `"deepseek"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `temperature: Optional[float]` The temperature of the model. - `class TogetherModelSettings: …` Together AI model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["together"]]` The type of the provider. - `"together"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `temperature: Optional[float]` The temperature of the model. - `class BedrockModelSettings: …` AWS Bedrock model configuration. - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["bedrock"]]` The type of the provider. - `"bedrock"` - `response_format: Optional[ResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `temperature: Optional[float]` The temperature of the model. - `class CompactionSettingsModelSettingsBasetenModelSettings: …` Baseten model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["baseten"]]` The type of the provider. - `"baseten"` - `temperature: Optional[float]` The temperature of the model. - `class CompactionSettingsModelSettingsOpenRouterModelSettings: …` OpenRouter model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["openrouter"]]` The type of the provider. - `"openrouter"` - `response_format: Optional[CompactionSettingsModelSettingsOpenRouterModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `temperature: Optional[float]` The temperature of the model. - `class CompactionSettingsModelSettingsChatGptoAuthModelSettings: …` ChatGPT OAuth model configuration (uses ChatGPT backend API). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["chatgpt_oauth"]]` The type of the provider. - `"chatgpt_oauth"` - `reasoning: Optional[CompactionSettingsModelSettingsChatGptoAuthModelSettingsReasoning]` The reasoning configuration for the model. - `reasoning_effort: Optional[Literal["none", "low", "medium", 2 more]]` The reasoning effort level for GPT-5.x and o-series models. - `"none"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `temperature: Optional[float]` The temperature of the model. - `prompt: Optional[str]` The prompt to use for summarization. If None, uses mode-specific default. - `prompt_acknowledgement: Optional[bool]` Whether to include an acknowledgement post-prompt (helps prevent non-summary outputs). - `sliding_window_percentage: Optional[float]` The percentage of the context window to keep post-summarization (only used in sliding window modes). - `created_at: Optional[datetime]` The timestamp when the object was created. - `created_by_id: Optional[str]` The id of the user that made this object. - `deployment_id: Optional[str]` The id of the deployment. - `description: Optional[str]` The description of the agent. - `embedding: Optional[str]` The embedding model handle used by the agent (format: provider/model-name). - `embedding_config: Optional[EmbeddingConfig]` Configuration for embedding model connection and processing parameters. - `enable_sleeptime: Optional[bool]` If set to True, memory management will move to a background agent thread. - `entity_id: Optional[str]` The id of the entity within the template. - `hidden: Optional[bool]` If set to True, the agent will be hidden. - `identities: Optional[List[Identity]]` The identities associated with this agent. - `id: str` The human-friendly ID of the Identity - `agent_ids: List[str]` The IDs of the agents associated with the identity. - `block_ids: List[str]` The IDs of the blocks associated with the identity. - `identifier_key: str` External, user-generated identifier key of the identity. - `identity_type: Literal["org", "user", "other"]` The type of the identity. - `"org"` - `"user"` - `"other"` - `name: str` The name of the identity. - `project_id: Optional[str]` The project id of the identity, if applicable. - `properties: Optional[List[IdentityProperty]]` List of properties associated with the identity - `key: str` The key of the property - `type: Literal["string", "number", "boolean", "json"]` The type of the property - `"string"` - `"number"` - `"boolean"` - `"json"` - `value: Union[str, float, bool, Dict[str, object]]` The value of the property - `str` - `float` - `bool` - `Dict[str, object]` - `identity_ids: Optional[List[str]]` Deprecated: Use `identities` field instead. The ids of the identities associated with this agent. - `last_run_completion: Optional[datetime]` The timestamp when the agent last completed a run. - `last_run_duration_ms: Optional[int]` The duration in milliseconds of the agent's last run. - `last_stop_reason: Optional[StopReasonType]` The stop reason from the agent's last run. - `"end_turn"` - `"error"` - `"llm_api_error"` - `"invalid_llm_response"` - `"invalid_tool_call"` - `"max_steps"` - `"max_tokens_exceeded"` - `"no_tool_call"` - `"tool_rule"` - `"cancelled"` - `"insufficient_credits"` - `"requires_approval"` - `"context_window_overflow_in_system_prompt"` - `last_updated_by_id: Optional[str]` The id of the user that made this object. - `managed_group: Optional[ManagedGroup]` The multi-agent group that this agent manages - `id: str` The id of the group. Assigned by the database. - `agent_ids: List[str]` - `description: str` - `manager_type: Literal["round_robin", "supervisor", "dynamic", 3 more]` - `"round_robin"` - `"supervisor"` - `"dynamic"` - `"sleeptime"` - `"voice_sleeptime"` - `"swarm"` - `base_template_id: Optional[str]` The base template id. - `deployment_id: Optional[str]` The id of the deployment. - `hidden: Optional[bool]` If set to True, the group will be hidden. - `last_processed_message_id: Optional[str]` - `manager_agent_id: Optional[str]` - `max_message_buffer_length: Optional[int]` The desired maximum length of messages in the context window of the convo agent. This is a best effort, and may be off slightly due to user/assistant interleaving. - `max_turns: Optional[int]` - `min_message_buffer_length: Optional[int]` The desired minimum length of messages in the context window of the convo agent. This is a best effort, and may be off-by-one due to user/assistant interleaving. - `project_id: Optional[str]` The associated project id. - `shared_block_ids: Optional[List[str]]` - `sleeptime_agent_frequency: Optional[int]` - `template_id: Optional[str]` The id of the template. - `termination_token: Optional[str]` - `turns_counter: Optional[int]` - `max_files_open: Optional[int]` Maximum number of files that can be open at once for this agent. Setting this too high may exceed the context window, which will break the agent. - `message_buffer_autoclear: Optional[bool]` If set to True, the agent will not remember previous messages (though the agent will still retain state via core memory blocks and archival/recall memory). Not recommended unless you have an advanced use case. - `message_ids: Optional[List[str]]` The ids of the messages in the agent's in-context memory. - `metadata: Optional[Dict[str, object]]` The metadata of the agent. - `model: Optional[str]` The model handle used by the agent (format: provider/model-name). - `model_settings: Optional[ModelSettings]` The model settings used by the agent. - `class OpenAIModelSettings: …` - `class ModelSettingsSgLangModelSettings: …` SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["sglang"]]` The type of the provider. - `"sglang"` - `reasoning: Optional[ModelSettingsSgLangModelSettingsReasoning]` The reasoning configuration for the model. - `reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]` The reasoning effort to use when generating text reasoning models - `"none"` - `"minimal"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `response_format: Optional[ModelSettingsSgLangModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `strict: Optional[bool]` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature: Optional[float]` The temperature of the model. - `tool_call_parser: Optional[str]` SGLang tool call parser name (for example 'glm47', 'qwen25', or 'hermes'). - `class AnthropicModelSettings: …` - `class GoogleAIModelSettings: …` - `class GoogleVertexModelSettings: …` - `class AzureModelSettings: …` Azure OpenAI model configuration (OpenAI-compatible). - `class XaiModelSettings: …` xAI model configuration (OpenAI-compatible). - `class ModelSettingsMoonshotModelSettings: …` Moonshot/Kimi model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["moonshot"]]` The type of the provider. - `"moonshot"` - `response_format: Optional[ModelSettingsMoonshotModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `strict: Optional[bool]` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature: Optional[float]` The temperature of the model. - `class ModelSettingsZaiModelSettings: …` Z.ai (ZhipuAI) model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["zai"]]` The type of the provider. - `"zai"` - `response_format: Optional[ModelSettingsZaiModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `temperature: Optional[float]` The temperature of the model. - `thinking: Optional[ModelSettingsZaiModelSettingsThinking]` The thinking configuration for GLM-4.5+ models. - `clear_thinking: Optional[bool]` If False, preserved thinking is used (recommended for agents). - `type: Optional[Literal["enabled", "disabled"]]` Whether thinking is enabled or disabled. - `"enabled"` - `"disabled"` - `class ModelSettingsMoonshotCodingModelSettings: …` Kimi Code model configuration (Anthropic-compatible). - `effort: Optional[Literal["low", "medium", "high", 2 more]]` Effort level for supported Anthropic models (controls token spending). 'xhigh' and 'max' are available on Opus 4.6+. Not setting this gives similar performance to 'high'. - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `"max"` - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["moonshot_coding"]]` The type of the provider. - `"moonshot_coding"` - `response_format: Optional[ModelSettingsMoonshotCodingModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `strict: Optional[bool]` Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas. - `temperature: Optional[float]` The temperature of the model. - `thinking: Optional[ModelSettingsMoonshotCodingModelSettingsThinking]` The thinking configuration for the model. - `budget_tokens: Optional[int]` The maximum number of tokens the model can use for extended thinking. - `type: Optional[Literal["enabled", "disabled"]]` The type of thinking to use. - `"enabled"` - `"disabled"` - `verbosity: Optional[Literal["low", "medium", "high"]]` Soft control for how verbose model output should be, used for GPT-5 models. - `"low"` - `"medium"` - `"high"` - `class GroqModelSettings: …` Groq model configuration (OpenAI-compatible). - `class DeepseekModelSettings: …` Deepseek model configuration (OpenAI-compatible). - `class TogetherModelSettings: …` Together AI model configuration (OpenAI-compatible). - `class BedrockModelSettings: …` AWS Bedrock model configuration. - `class ModelSettingsBasetenModelSettings: …` Baseten model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["baseten"]]` The type of the provider. - `"baseten"` - `temperature: Optional[float]` The temperature of the model. - `class ModelSettingsOpenRouterModelSettings: …` OpenRouter model configuration (OpenAI-compatible). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["openrouter"]]` The type of the provider. - `"openrouter"` - `response_format: Optional[ModelSettingsOpenRouterModelSettingsResponseFormat]` The response format for the model. - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `temperature: Optional[float]` The temperature of the model. - `class ModelSettingsChatGptoAuthModelSettings: …` ChatGPT OAuth model configuration (uses ChatGPT backend API). - `max_output_tokens: Optional[int]` The maximum number of tokens the model can generate. - `parallel_tool_calls: Optional[bool]` Whether to enable parallel tool calling. - `provider_type: Optional[Literal["chatgpt_oauth"]]` The type of the provider. - `"chatgpt_oauth"` - `reasoning: Optional[ModelSettingsChatGptoAuthModelSettingsReasoning]` The reasoning configuration for the model. - `reasoning_effort: Optional[Literal["none", "low", "medium", 2 more]]` The reasoning effort level for GPT-5.x and o-series models. - `"none"` - `"low"` - `"medium"` - `"high"` - `"xhigh"` - `temperature: Optional[float]` The temperature of the model. - `multi_agent_group: Optional[MultiAgentGroup]` Deprecated: Use `managed_group` field instead. The multi-agent group that this agent manages. - `id: str` The id of the group. Assigned by the database. - `agent_ids: List[str]` - `description: str` - `manager_type: Literal["round_robin", "supervisor", "dynamic", 3 more]` - `"round_robin"` - `"supervisor"` - `"dynamic"` - `"sleeptime"` - `"voice_sleeptime"` - `"swarm"` - `base_template_id: Optional[str]` The base template id. - `deployment_id: Optional[str]` The id of the deployment. - `hidden: Optional[bool]` If set to True, the group will be hidden. - `last_processed_message_id: Optional[str]` - `manager_agent_id: Optional[str]` - `max_message_buffer_length: Optional[int]` The desired maximum length of messages in the context window of the convo agent. This is a best effort, and may be off slightly due to user/assistant interleaving. - `max_turns: Optional[int]` - `min_message_buffer_length: Optional[int]` The desired minimum length of messages in the context window of the convo agent. This is a best effort, and may be off-by-one due to user/assistant interleaving. - `project_id: Optional[str]` The associated project id. - `shared_block_ids: Optional[List[str]]` - `sleeptime_agent_frequency: Optional[int]` - `template_id: Optional[str]` The id of the template. - `termination_token: Optional[str]` - `turns_counter: Optional[int]` - `pending_approval: Optional[ApprovalRequestMessage]` A message representing a request for approval to call a tool (generated by the LLM to trigger tool execution). Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message tool_call (ToolCall): The tool call - `id: str` - `date: datetime` - `tool_call: ToolCall` The tool call that has been requested by the llm to run - `class ToolCall: …` - `arguments: str` - `name: str` - `tool_call_id: str` - `class ToolCallDelta: …` - `arguments: Optional[str]` - `name: Optional[str]` - `tool_call_id: Optional[str]` - `is_err: Optional[bool]` - `message_type: Optional[Literal["approval_request_message"]]` The type of the message. - `"approval_request_message"` - `name: Optional[str]` - `otid: Optional[str]` The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs. - `run_id: Optional[str]` - `sender_id: Optional[str]` - `seq_id: Optional[int]` - `step_id: Optional[str]` - `tool_calls: Optional[ToolCalls]` The tool calls that have been requested by the llm to run, which are pending approval - `List[ToolCall]` - `arguments: str` - `name: str` - `tool_call_id: str` - `class ToolCallDelta: …` - `per_file_view_window_char_limit: Optional[int]` The per-file view window character limit for this agent. Setting this too high may exceed the context window, which will break the agent. - `project_id: Optional[str]` The id of the project the agent belongs to. - `response_format: Optional[ResponseFormat]` The response format used by the agent - `class TextResponseFormat: …` Response format for plain text responses. - `class JsonSchemaResponseFormat: …` Response format for JSON schema-based responses. - `class JsonObjectResponseFormat: …` Response format for JSON object responses. - `secrets: Optional[List[AgentEnvironmentVariable]]` The environment variables for tool execution specific to this agent. - `agent_id: str` The ID of the agent this environment variable belongs to. - `key: str` The name of the environment variable. - `value: str` The value of the environment variable. - `id: Optional[str]` The human-friendly ID of the Agent-env - `created_at: Optional[datetime]` The timestamp when the object was created. - `created_by_id: Optional[str]` The id of the user that made this object. - `description: Optional[str]` An optional description of the environment variable. - `last_updated_by_id: Optional[str]` The id of the user that made this object. - `updated_at: Optional[datetime]` The timestamp when the object was last updated. - `value_enc: Optional[str]` Encrypted secret value (stored as encrypted string) - `template_id: Optional[str]` The id of the template the agent belongs to. - `timezone: Optional[str]` The timezone of the agent (IANA format). - `tool_exec_environment_variables: Optional[List[AgentEnvironmentVariable]]` Deprecated: use `secrets` field instead. - `agent_id: str` The ID of the agent this environment variable belongs to. - `key: str` The name of the environment variable. - `value: str` The value of the environment variable. - `id: Optional[str]` The human-friendly ID of the Agent-env - `created_at: Optional[datetime]` The timestamp when the object was created. - `created_by_id: Optional[str]` The id of the user that made this object. - `description: Optional[str]` An optional description of the environment variable. - `last_updated_by_id: Optional[str]` The id of the user that made this object. - `updated_at: Optional[datetime]` The timestamp when the object was last updated. - `value_enc: Optional[str]` Encrypted secret value (stored as encrypted string) - `tool_rules: Optional[List[ToolRule]]` The list of tool rules. - `class ChildToolRule: …` A ToolRule represents a tool that can be invoked by the agent. - `children: List[str]` The children tools that can be invoked. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `child_arg_nodes: Optional[List[ChildArgNode]]` Optional list of typed child argument overrides. Each node must reference a child in 'children'. - `name: str` The name of the child tool to invoke next. - `args: Optional[Dict[str, object]]` Optional prefilled arguments for this child tool. Keys must match the tool's parameter names and values must satisfy the tool's JSON schema. Supports partial prefill; non-overlapping parameters are left to the model. - `prompt_template: Optional[str]` Optional template string (ignored). - `type: Optional[Literal["constrain_child_tools"]]` - `"constrain_child_tools"` - `class InitToolRule: …` Represents the initial tool rule configuration. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `args: Optional[Dict[str, object]]` Optional prefilled arguments for this tool. When present, these values will override any LLM-provided arguments with the same keys during invocation. Keys must match the tool's parameter names and values must satisfy the tool's JSON schema. Supports partial prefill; non-overlapping parameters are left to the model. - `prompt_template: Optional[str]` Optional template string (ignored). Rendering uses fast built-in formatting for performance. - `type: Optional[Literal["run_first"]]` - `"run_first"` - `class TerminalToolRule: …` Represents a terminal tool rule configuration where if this tool gets called, it must end the agent loop. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `prompt_template: Optional[str]` Optional template string (ignored). - `type: Optional[Literal["exit_loop"]]` - `"exit_loop"` - `class ConditionalToolRule: …` A ToolRule that conditionally maps to different child tools based on the output. - `child_output_mapping: Dict[str, str]` The output case to check for mapping - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `default_child: Optional[str]` The default child tool to be called. If None, any tool can be called. - `prompt_template: Optional[str]` Optional template string (ignored). - `require_output_mapping: Optional[bool]` Whether to throw an error when output doesn't match any case - `type: Optional[Literal["conditional"]]` - `"conditional"` - `class ContinueToolRule: …` Represents a tool rule configuration where if this tool gets called, it must continue the agent loop. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `prompt_template: Optional[str]` Optional template string (ignored). - `type: Optional[Literal["continue_loop"]]` - `"continue_loop"` - `class RequiredBeforeExitToolRule: …` Represents a tool rule configuration where this tool must be called before the agent loop can exit. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `prompt_template: Optional[str]` Optional template string (ignored). - `type: Optional[Literal["required_before_exit"]]` - `"required_before_exit"` - `class MaxCountPerStepToolRule: …` Represents a tool rule configuration which constrains the total number of times this tool can be invoked in a single step. - `max_count_limit: int` The max limit for the total number of times this tool can be invoked in a single step. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `prompt_template: Optional[str]` Optional template string (ignored). - `type: Optional[Literal["max_count_per_step"]]` - `"max_count_per_step"` - `class ParentToolRule: …` A ToolRule that only allows a child tool to be called if the parent has been called. - `children: List[str]` The children tools that can be invoked. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `prompt_template: Optional[str]` Optional template string (ignored). - `type: Optional[Literal["parent_last_tool"]]` - `"parent_last_tool"` - `class RequiresApprovalToolRule: …` Represents a tool rule configuration which requires approval before the tool can be invoked. - `tool_name: str` The name of the tool. Must exist in the database for the user's organization. - `prompt_template: Optional[str]` Optional template string (ignored). Rendering uses fast built-in formatting for performance. - `type: Optional[Literal["requires_approval"]]` - `"requires_approval"` - `updated_at: Optional[datetime]` The timestamp when the object was last updated. - `func_return: Optional[object]` The function return object - `sandbox_config_fingerprint: Optional[str]` The fingerprint of the config for the sandbox - `stderr: Optional[List[str]]` Captured stderr from the function invocation - `stdout: Optional[List[str]]` Captured stdout (prints, logs) from function invocation ### Example ```python import os from letta_client import Letta client = Letta( api_key=os.environ.get("LETTA_API_KEY"), # This is the default and can be omitted ) tool_execution_result = client.mcp_servers.tools.run( tool_id="tool_id", mcp_server_id="mcp_server_id", ) print(tool_execution_result.status) ``` #### Response ```json { "status": "success", "agent_state": { "id": "id", "agent_type": "memgpt_agent", "blocks": [ { "value": "value", "id": "block-123e4567-e89b-12d3-a456-426614174000", "base_template_id": "base_template_id", "created_by_id": "created_by_id", "deployment_id": "deployment_id", "description": "description", "entity_id": "entity_id", "hidden": true, "is_template": true, "label": "label", "last_updated_by_id": "last_updated_by_id", "limit": 0, "metadata": { "foo": "bar" }, "preserve_on_migration": true, "project_id": "project_id", "read_only": true, "tags": [ "string" ], "template_id": "template_id", "template_name": "template_name" } ], "llm_config": { "context_window": 0, "model": "model", "model_endpoint_type": "openai", "compatibility_type": "gguf", "display_name": "display_name", "effort": "low", "enable_reasoner": true, "frequency_penalty": 0, "handle": "handle", "max_reasoning_tokens": 0, "max_tokens": 0, "model_endpoint": "model_endpoint", "model_wrapper": "model_wrapper", "parallel_tool_calls": true, "provider_category": "base", "provider_name": "provider_name", "put_inner_thoughts_in_kwargs": true, "reasoning_effort": "none", "response_format": { "type": "text" }, "return_logprobs": true, "return_token_ids": true, "strict": true, "temperature": 0, "tier": "tier", "tool_call_parser": "tool_call_parser", "top_logprobs": 0, "verbosity": "low" }, "memory": { "blocks": [ { "value": "value", "id": "block-123e4567-e89b-12d3-a456-426614174000", "base_template_id": "base_template_id", "created_by_id": "created_by_id", "deployment_id": "deployment_id", "description": "description", "entity_id": "entity_id", "hidden": true, "is_template": true, "label": "label", "last_updated_by_id": "last_updated_by_id", "limit": 0, "metadata": { "foo": "bar" }, "preserve_on_migration": true, "project_id": "project_id", "read_only": true, "tags": [ "string" ], "template_id": "template_id", "template_name": "template_name" } ], "agent_type": "memgpt_agent", "file_blocks": [ { "file_id": "file_id", "is_open": true, "source_id": "source_id", "value": "value", "id": "block-123e4567-e89b-12d3-a456-426614174000", "base_template_id": "base_template_id", "created_by_id": "created_by_id", "deployment_id": "deployment_id", "description": "description", "entity_id": "entity_id", "hidden": true, "is_template": true, "label": "label", "last_accessed_at": "2019-12-27T18:11:19.117Z", "last_updated_by_id": "last_updated_by_id", "limit": 0, "metadata": { "foo": "bar" }, "preserve_on_migration": true, "project_id": "project_id", "read_only": true, "tags": [ "string" ], "template_id": "template_id", "template_name": "template_name" } ], "git_enabled": true, "prompt_template": "prompt_template" }, "name": "name", "sources": [ { "id": "source-123e4567-e89b-12d3-a456-426614174000", "embedding_config": { "embedding_dim": 0, "embedding_endpoint_type": "openai", "embedding_model": "embedding_model", "azure_deployment": "azure_deployment", "azure_endpoint": "azure_endpoint", "azure_version": "azure_version", "batch_size": 0, "embedding_chunk_size": 0, "embedding_endpoint": "embedding_endpoint", "handle": "handle" }, "name": "name", "created_at": "2019-12-27T18:11:19.117Z", "created_by_id": "created_by_id", "description": "description", "instructions": "instructions", "last_updated_by_id": "last_updated_by_id", "metadata": { "foo": "bar" }, "updated_at": "2019-12-27T18:11:19.117Z", "vector_db_provider": "native" } ], "system": "system", "tags": [ "string" ], "tools": [ { "id": "tool-123e4567-e89b-12d3-a456-426614174000", "args_json_schema": { "foo": "bar" }, "created_by_id": "created_by_id", "default_requires_approval": true, "description": "description", "enable_parallel_execution": true, "json_schema": { "foo": "bar" }, "last_updated_by_id": "last_updated_by_id", "metadata_": { "foo": "bar" }, "name": "name", "npm_requirements": [ { "name": "x", "version": "version" } ], "pip_requirements": [ { "name": "x", "version": "version" } ], "project_id": "project_id", "return_char_limit": 1, "source_code": "source_code", "source_type": "source_type", "tags": [ "string" ], "tool_type": "custom" } ], "base_template_id": "base_template_id", "compaction_settings": { "clip_chars": 0, "mode": "all", "model": "model", "model_settings": { "max_output_tokens": 0, "parallel_tool_calls": true, "provider_type": "openai", "reasoning": { "reasoning_effort": "none" }, "response_format": { "type": "text" }, "strict": true, "temperature": 0 }, "prompt": "prompt", "prompt_acknowledgement": true, "sliding_window_percentage": 0 }, "created_at": "2019-12-27T18:11:19.117Z", "created_by_id": "created_by_id", "deployment_id": "deployment_id", "description": "description", "embedding": "embedding", "embedding_config": { "embedding_dim": 0, "embedding_endpoint_type": "openai", "embedding_model": "embedding_model", "azure_deployment": "azure_deployment", "azure_endpoint": "azure_endpoint", "azure_version": "azure_version", "batch_size": 0, "embedding_chunk_size": 0, "embedding_endpoint": "embedding_endpoint", "handle": "handle" }, "enable_sleeptime": true, "entity_id": "entity_id", "hidden": true, "identities": [ { "id": "identity-123e4567-e89b-12d3-a456-426614174000", "agent_ids": [ "string" ], "block_ids": [ "string" ], "identifier_key": "identifier_key", "identity_type": "org", "name": "name", "project_id": "project_id", "properties": [ { "key": "key", "type": "string", "value": "string" } ] } ], "identity_ids": [ "string" ], "last_run_completion": "2019-12-27T18:11:19.117Z", "last_run_duration_ms": 0, "last_stop_reason": "end_turn", "last_updated_by_id": "last_updated_by_id", "managed_group": { "id": "id", "agent_ids": [ "string" ], "description": "description", "manager_type": "round_robin", "base_template_id": "base_template_id", "deployment_id": "deployment_id", "hidden": true, "last_processed_message_id": "last_processed_message_id", "manager_agent_id": "manager_agent_id", "max_message_buffer_length": 0, "max_turns": 0, "min_message_buffer_length": 0, "project_id": "project_id", "shared_block_ids": [ "string" ], "sleeptime_agent_frequency": 0, "template_id": "template_id", "termination_token": "termination_token", "turns_counter": 0 }, "max_files_open": 0, "message_buffer_autoclear": true, "message_ids": [ "string" ], "metadata": { "foo": "bar" }, "model": "model", "model_settings": { "max_output_tokens": 0, "parallel_tool_calls": true, "provider_type": "openai", "reasoning": { "reasoning_effort": "none" }, "response_format": { "type": "text" }, "strict": true, "temperature": 0 }, "multi_agent_group": { "id": "id", "agent_ids": [ "string" ], "description": "description", "manager_type": "round_robin", "base_template_id": "base_template_id", "deployment_id": "deployment_id", "hidden": true, "last_processed_message_id": "last_processed_message_id", "manager_agent_id": "manager_agent_id", "max_message_buffer_length": 0, "max_turns": 0, "min_message_buffer_length": 0, "project_id": "project_id", "shared_block_ids": [ "string" ], "sleeptime_agent_frequency": 0, "template_id": "template_id", "termination_token": "termination_token", "turns_counter": 0 }, "pending_approval": { "id": "id", "date": "2019-12-27T18:11:19.117Z", "tool_call": { "arguments": "arguments", "name": "name", "tool_call_id": "tool_call_id" }, "is_err": true, "message_type": "approval_request_message", "name": "name", "otid": "otid", "run_id": "run_id", "sender_id": "sender_id", "seq_id": 0, "step_id": "step_id", "tool_calls": [ { "arguments": "arguments", "name": "name", "tool_call_id": "tool_call_id" } ] }, "per_file_view_window_char_limit": 0, "project_id": "project_id", "response_format": { "type": "text" }, "secrets": [ { "agent_id": "agent_id", "key": "key", "value": "value", "id": "agent-env-123e4567-e89b-12d3-a456-426614174000", "created_at": "2019-12-27T18:11:19.117Z", "created_by_id": "created_by_id", "description": "description", "last_updated_by_id": "last_updated_by_id", "updated_at": "2019-12-27T18:11:19.117Z", "value_enc": "value_enc" } ], "template_id": "template_id", "timezone": "timezone", "tool_exec_environment_variables": [ { "agent_id": "agent_id", "key": "key", "value": "value", "id": "agent-env-123e4567-e89b-12d3-a456-426614174000", "created_at": "2019-12-27T18:11:19.117Z", "created_by_id": "created_by_id", "description": "description", "last_updated_by_id": "last_updated_by_id", "updated_at": "2019-12-27T18:11:19.117Z", "value_enc": "value_enc" } ], "tool_rules": [ { "children": [ "string" ], "tool_name": "tool_name", "child_arg_nodes": [ { "name": "name", "args": { "foo": "bar" } } ], "prompt_template": "prompt_template", "type": "constrain_child_tools" } ], "updated_at": "2019-12-27T18:11:19.117Z" }, "func_return": {}, "sandbox_config_fingerprint": "sandbox_config_fingerprint", "stderr": [ "string" ], "stdout": [ "string" ] } ```