langchain-agentfetch 0.1.0

LangChain Tool wrapper for AgentFetch — token-budgeted web fetch for AI agents.

langchain-agentfetch

Drop-in LangChain Tool wrappers for AgentFetch — token-budgeted web fetch for AI agents.

Stop building your own web fetch / token-truncation / cache layer for every LangChain agent. AgentFetch handles routing (Trafilatura → Jina → FireCrawl → PDF), caching (6h Redis), and token budgeting in one tool.

Install

pip install langchain-agentfetch

Quick start

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

import os
from langchain_agentfetch import AgentFetchTool

os.environ["AGENTFETCH_API_KEY"] = "af_xxx"

tool = AgentFetchTool()
result = tool.run({"url": "https://news.ycombinator.com", "max_tokens": 2000})
print(result)

All four tools

Tool	When to use
AgentFetchTool (fetch_url)	You have a specific URL to fetch
EstimateTokensTool	You want to know if a URL fits your context window before fetching
FetchMultipleTool	You have multiple URLs (search results, link lists)
SearchAndFetchTool	You have a research question, not specific URLs

Use the toolkit (recommended for agents)

from langchain_openai import ChatOpenAI
from langchain.agents import AgentExecutor, create_tool_calling_agent
from langchain_core.prompts import ChatPromptTemplate
from langchain_agentfetch import AgentFetchToolkit

toolkit = AgentFetchToolkit(api_key="af_xxx")
tools = toolkit.get_tools()

prompt = ChatPromptTemplate.from_messages([
    ("system", "You are a research assistant. Use AgentFetch tools to read web pages "
               "and answer questions. Always estimate tokens before fetching long URLs."),
    ("user", "{input}"),
    ("placeholder", "{agent_scratchpad}"),
])

llm = ChatOpenAI(model="gpt-4o-mini")
agent = create_tool_calling_agent(llm, tools, prompt)
executor = AgentExecutor(agent=agent, tools=tools)

executor.invoke({"input": "What's on the Hacker News front page right now?"})

The agent will:

1. Use agentfetch_search_and_fetch or agentfetch_fetch_url to get the page
2. Get clean Markdown back, already token-truncated
3. Reason over it without blowing the context window

Configuration

Env var	Default	Notes
AGENTFETCH_API_KEY	required	Get one free at agentfetch.dev
AGENTFETCH_BASE_URL	https://api.agentfetch.dev	Override only if self-hosting

You can also pass api_key= and base_url= directly to any Tool / Toolkit constructor.

Why a token-aware fetch tool

LangChain's default tools (like requests_get) return raw HTML/JSON with no truncation, no awareness of your context budget, and no caching. That works at toy scale; it falls over the moment your agent fetches a 50KB news article into a 4K context window.

AgentFetch was built for that case:

• Pre-fetch token estimation so the agent can skip a URL it can't afford
• Server-side max_tokens truncation before the response leaves the API
• 6-hour cache for repeat fetches (~$0.0001 each)
• Auto-routing so the agent doesn't pick between Jina, FireCrawl, and pypdf manually

Pricing

Same pay-per-call pricing as the AgentFetch API: from $0.001/fetch, 500 free on signup. No subscription required. See agentfetch.dev/pricing.

License

MIT.