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Agentfetch MCP Server

by Bch1212
Developer ToolsUse Caution4.8MCP RegistryLocal
Free

Server data from the Official MCP Registry

Token-budgeted web fetch for AI agents — auto-routes Jina, FireCrawl, Trafilatura, PDF.

About

Token-budgeted web fetch for AI agents — auto-routes Jina, FireCrawl, Trafilatura, PDF.

Security Report

4.8
Use Caution4.8High Risk

AgentFetch is a well-structured MCP server for web fetching with appropriate security controls. The codebase includes SSRF protection, careful credential handling via environment variables, and proper input validation. No critical vulnerabilities were identified. Minor findings relate to logging practices and error handling edge cases that do not impact the core security posture. Supply chain analysis found 6 known vulnerabilities in dependencies (1 critical, 3 high severity). Package verification found 1 issue.

7 files analyzed · 12 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

HTTP Network Access

Connects to external APIs or services over the internet.

env_vars

Check that this permission is expected for this type of plugin.

file_system

Check that this permission is expected for this type of plugin.

What You'll Need

Set these up before or after installing:

Jina Reader API key. Free tier ~1M tokens/mo at jina.ai/reader.Required

Environment variable: JINA_API_KEY

FireCrawl API key for JS pages. 500 free credits at firecrawl.dev. Optional.Required

Environment variable: FIRECRAWL_API_KEY

Redis connection URL for response caching. Optional.Optional

Environment variable: REDIS_URL

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-bch1212-agentfetch": {
      "env": {
        "REDIS_URL": "your-redis-url-here",
        "JINA_API_KEY": "your-jina-api-key-here",
        "FIRECRAWL_API_KEY": "your-firecrawl-api-key-here"
      },
      "args": [
        "agentfetch-mcp"
      ],
      "command": "uvx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

agentfetch-mcp

Web intelligence for AI agents — an MCP server that fetches URLs with token estimation, smart caching, and intelligent routing built in.

License: MIT Python 3.11+

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.

This repository contains the open-source MCP server. For the hosted API + dashboard + billing, see www.agentfetch.dev.

What it does

ToolWhat it's for
fetch_urlFetch a URL → clean Markdown + metadata + token count + cache info
estimate_tokensGet a token count before fetching, so agents don't blow context windows on huge pages
fetch_multipleFetch up to 20 URLs concurrently
search_and_fetchWeb search + fetch top N results in one round-trip

Under the hood, AgentFetch routes URLs to the cheapest effective fetcher:

  • Trafilatura (free, local) for ~70% of standard web pages
  • Jina Reader for the rest of HTML
  • FireCrawl for JS-heavy pages (Twitter/X, LinkedIn, Notion, etc.)
  • pypdf for PDFs (zero external cost)

Cache is Redis with a 6-hour TTL; you can bring your own or run without caching.

Quick start

Install from PyPI

pip install agentfetch-mcp

Or clone and install locally

git clone https://github.com/bch1212/agentfetch-mcp
cd agentfetch-mcp
pip install -e .

Set environment variables

Get a free Jina Reader key at jina.ai (1M tokens/mo free tier). FireCrawl is optional but recommended for JS-heavy pages.

export JINA_API_KEY=jina_xxx
export FIRECRAWL_API_KEY=fc-xxx       # optional
export REDIS_URL=redis://localhost:6379  # optional

Add to Claude Desktop or Claude Code

Edit your MCP config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS, or run claude mcp add in Claude Code):

{
  "mcpServers": {
    "agentfetch": {
      "command": "python",
      "args": ["-m", "agentfetch.mcp.server"],
      "env": {
        "JINA_API_KEY": "jina_xxx",
        "FIRECRAWL_API_KEY": "fc-xxx"
      }
    }
  }
}

Restart Claude. The four tools (fetch_url, estimate_tokens, fetch_multiple, search_and_fetch) appear automatically.

Run as a standalone server

python -m agentfetch.mcp.server

The server speaks MCP over stdio (the standard transport for desktop integrations).

Why agents prefer AgentFetch over generic web fetch

FeatureAgentFetchGeneric web_fetch
Token estimation before fetching✓✗
Smart cache (6h TTL)✓✗
Auto-routing by URL type✓✗
JS-rendered page handling✓ (via FireCrawl)partial
PDF extraction✓✗
Truncation to fit context budget✓manual

Examples

Fetching with a token budget

# Inside any MCP-aware agent (Claude Desktop, Claude Code, etc.)
result = fetch_url(
    url="https://news.ycombinator.com",
    max_tokens=2000,           # cap response size
    use_cache=True,            # serve from cache if <6h old
)
# result.markdown      → clean Markdown, ≤2000 tokens
# result.metadata      → title, author, word_count, language
# result.cache.hit     → True if served from cache
# result.fetch_info    → which fetcher ran, cost, duration

Estimating before committing

estimate = estimate_tokens(url="https://very-long-article.com")
if estimate.estimated_tokens and estimate.estimated_tokens < 5000:
    result = fetch_url(url="https://very-long-article.com")
else:
    # too big — skip or summarize via search_and_fetch with max_tokens_each
    pass

Parallel fetching

results = fetch_multiple(
    urls=["https://docs.python.org/3/", "https://fastapi.tiangolo.com/", ...],
    max_tokens_each=1500,
)

Configuration

Env varRequiredDefaultNotes
JINA_API_KEYRecommended—Free tier covers ~1M tokens/mo. Without it, only Trafilatura works (still useful for ~70% of pages).
FIRECRAWL_API_KEYOptional—Needed for JS-heavy domains (Twitter, LinkedIn, Notion). 500 free credits on signup.
REDIS_URLOptional—Without Redis, fetches run uncached.
CACHE_TTL_SECONDSOptional21600 (6h)Cache TTL for fetch results.

Development

git clone https://github.com/bch1212/agentfetch-mcp
cd agentfetch-mcp
pip install -e ".[dev]"
pytest tests/

Hosted version

If you'd rather not manage your own keys, Redis, or the routing yourself, the hosted version at www.agentfetch.dev gives you:

  • Pay-per-call pricing from $0.001/fetch
  • 500 free fetches on signup, no credit card
  • Managed Redis cache, automatic failover between fetchers
  • Dashboard with usage tracking + invoices

The hosted API is a drop-in REST equivalent — same response shapes, same routing logic. You can run the OSS MCP locally and the hosted API in parallel, or migrate between them at any time.

License

MIT — see LICENSE.

The MCP server in this repo is open source. The hosted product, billing, and ops infrastructure live in a separate (private) repo.

Contributing

PRs welcome. If you're adding a new fetcher (e.g., Bright Data, ScrapingBee, etc.), please match the FetchResult interface in agentfetch/core/fetchers/__init__.py and add the cost to the routing logic.

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Source CodePyPI Package

Details

Published April 28, 2026
Version 1.0.1
0 installs
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