Token-budgeted web fetch for AI agents — auto-routes Jina, FireCrawl, Trafilatura, PDF.
Token-budgeted web fetch for AI agents — auto-routes Jina, FireCrawl, Trafilatura, PDF.
AgentFetch sits between your agent and the open web. Instead of integrating Jina, FireCrawl, pypdf, and your own caching layer separately, agents call one MCP tool and AgentFetch handles routing, caching, token budgeting, and clean Markdown extraction automatically.
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Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| fetch_url | Fetch a URL → clean Markdown + metadata + token count + cache info |
| estimate_tokens | Get a token count *before* fetching, so agents don't blow context windows on huge pages |
| fetch_multiple | Fetch up to 20 URLs concurrently |
| search_and_fetch | Web search + fetch top N results in one round-trip |
{
"mcpServers": {
"agentfetch": {
"command": "uvx",
"args": ["agentfetch-mcp"],
"env": {
"JINA_API_KEY": "your-value",
"FIRECRAWL_API_KEY": "your-value",
"REDIS_URL": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| JINA_API_KEY | Credential the server authenticates with. | Yes |
| FIRECRAWL_API_KEY | Credential the server authenticates with. | Yes |
| REDIS_URL | Endpoint or connection string the server talks to. | Yes |
Retrieve public web pages as readable Markdown with the reference Fetch MCP server, including pagination for longer responses.
Use Firecrawl MCP to retrieve website content and extract information for research through Firecrawl’s API-backed web tools.
The original Chromium automation reference server — simple, screenshot-driven browser control.
Puppeteer-powered browser control that drives pages from the accessibility tree instead of pixels.
Automates browsers and APIs, enabling Large Language Models (LLMs) to interact with web pages for tasks like screenshot capture and JavaScript
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.