LlamaIndex Tools Integration: ContextFetch

pip install llama-index-tools-contextfetch

This tool connects agents to ContextFetch, a web search and web page to Markdown API.

Pass api_key, or set the CONTEXTFETCH_API_KEY environment variable. With neither, requests use ContextFetch's keyless tier, a small daily allowance per IP. The contextfetch package can request a free starter key: from contextfetch import ContextFetch; ContextFetch().free_key().

Usage

# %pip install llama-index llama-index-tools-contextfetch

from llama_index.tools.contextfetch import ContextFetchToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

contextfetch_tool = ContextFetchToolSpec()  # or ContextFetchToolSpec(api_key="...")
agent = FunctionAgent(
    tools=contextfetch_tool.to_tool_list(),
    llm=OpenAI(model="gpt-4.1"),
)

print(await agent.run("How do asyncio task groups handle errors?"))

Available Functions

search: Search the web. Returns each result's title, URL, published date when known, and the passages relevant to the query.

read_page: Read a web page as Markdown. With query, only the parts of the page relevant to it are returned.

find_similar: Find pages on other sites that are similar to a given page.

answer: Answer a question with passages quoted verbatim from web pages, each followed by [n], then the numbered source URLs. No text is generated.

Each function returns a Markdown string that names its sources by title and URL. To load pages as Documents for indexing, use llama-index-readers-contextfetch.

This loader is designed to be used as a way to load data as a Tool in an Agent.