LlamaIndex Tools Integration: Keenable

Keenable is a web search and page-fetch API built for AI agents. This package provides KeenableToolSpec, a LlamaIndex tool spec with two tools, search and fetch, usable from any LlamaIndex agent.

Keyless by default: with no API key the keyless public endpoints are used. Provide a key to use the authenticated endpoints (for higher rate limits).

Install

pip install llama-index-tools-keenable

Usage

from llama_index.tools.keenable import KeenableToolSpec
from llama_index.agent.openai import OpenAIAgent

# No api_key -> keyless public endpoints. Pass api_key=... or set
# KEENABLE_API_KEY to use the authenticated endpoints.
keenable_tool = KeenableToolSpec()

agent = OpenAIAgent.from_tools(keenable_tool.to_tool_list())
agent.chat("Find recent TypeScript best practices and summarize the top result")

Call the tools directly:

docs = keenable_tool.search("typescript best practices", site="github.com")
page = keenable_tool.fetch(docs[0].metadata["url"])
print(page[0].text)

search accepts optional per-query filters (site, published_after/before, acquired_after/before, mode) and returns one Document per result. fetch returns the page's main content as markdown. There is no max_results argument: the API returns a fixed-size result set as-is.

Configuration

• API key (optional). Constructor api_key=... or the KEENABLE_API_KEY environment variable. Blank → keyless public endpoints.
• Endpoint (optional). KEENABLE_API_URL overrides the base URL (HTTPS enforced; plain http only for loopback). The endpoint is never a tool argument the model can set, so it cannot be used to redirect requests.

The fetch tool rejects non-http(s) schemes and private/internal hosts client-side before sending.

License

MIT © Keenable