Fetch Webpage

The fetch_webpage tool enables Letta agents to fetch and convert webpages into readable text or markdown format. Useful for reading documentation, articles, and web content.

Quick Start

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from letta import Letta
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client = Letta(token="LETTA_API_KEY")
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agent = client.agents.create(
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    model="openai/gpt-4o",
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    tools=["fetch_webpage"],
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    memory_blocks=[{
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        "label": "persona",
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        "value": "I can fetch and read webpages to answer questions about online content."
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    }]
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)

Tool Parameters

Return Format

The tool returns webpage content as text/markdown.

With Exa API (if configured):

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{
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  "title": "Page title",
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  "published_date": "2025-01-15",
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  "author": "Author name",
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  "text": "Full page content in markdown"
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}

Fallback (without Exa): Returns markdown-formatted text extracted from the HTML.

How It Works

The tool uses a multi-tier approach:

1. Exa API (if EXA_API_KEY is configured): Uses Exa’s content extraction
2. Trafilatura (fallback): Open-source text extraction to markdown
3. Readability + html2text (final fallback): HTML cleaning and conversion

Self-Hosted Setup

For enhanced fetching on self-hosted servers, optionally configure an Exa API key. Without it, the tool still works using open-source extraction.

Optional: Configure Exa

$
docker run \
>
  -e EXA_API_KEY="your_exa_api_key" \
>
  letta/letta:latest

Common Patterns

Documentation Reader

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agent = client.agents.create(
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    model="openai/gpt-4o",
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    tools=["fetch_webpage", "web_search"],
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    memory_blocks=[{
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        "label": "persona",
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        "value": "I search for documentation with web_search and read it with fetch_webpage."
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    }]
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)

Research Assistant

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agent = client.agents.create(
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    model="openai/gpt-4o",
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    tools=["fetch_webpage", "archival_memory_insert"],
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    memory_blocks=[{
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        "label": "persona",
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        "value": "I fetch articles and store key insights in archival memory for later reference."
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    }]
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)

Content Summarizer

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agent = client.agents.create(
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    model="openai/gpt-4o",
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    tools=["fetch_webpage"],
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    memory_blocks=[{
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        "label": "persona",
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        "value": "I fetch webpages and provide summaries of their content."
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    }]
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)

When to Use

Related Documentation

• Utilities Overview
• Web Search
• Run Code
• Custom Tools
• Tool Variables