Examples →

Fetch a Wikipedia article for an AI agent

Wikipedia's HTML is dense with side panels and references. AgentFetch's cleaner strips them, returning just the article body in Markdown — perfect for fact-checking and RAG ingestion.

Try it

Get a free key at agentfetch.dev (500 free fetches/mo, no credit card).

curl -X POST https://api.agentfetch.dev/fetch \
  -H "Content-Type: application/json" \
  -H "X-AgentFetch-Key: af_xxx" \
  -d '{
    "url": "https://en.wikipedia.org/wiki/Anthropic",
    "max_tokens": 2000
  }'

In an MCP-aware agent

fetch_url(
  url="https://en.wikipedia.org/wiki/Anthropic",
  max_tokens=2000,
)

In LangChain

from langchain_agentfetch import AgentFetchTool

tool = AgentFetchTool(api_key="af_xxx")
result = tool.run({"url": "https://en.wikipedia.org/wiki/Anthropic"})

How it routes

AgentFetch automatically routes fetch wikipedia-style URLs through Trafilatura based on domain heuristics — you don't pick a fetcher.

When agents reach for this

Fact-checking, RAG ingestion, encyclopedia knowledge.

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