> ## Documentation Index
> Fetch the complete documentation index at: https://kestrel.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Kestrel Search

> Local web search, page extraction, and relevance ranking for AI coding agents.

# Kestrel Search

Kestrel Search gives coding assistants a local, keyless web-search capability.

It searches DuckDuckGo, Bing, or Yahoo, retrieves readable page content, and
re-ranks results with BM25. It works from the command line and provides
structured JSON output for agents and scripts.

Use it when an agent needs current documentation, release information, standards,
or other public web content without leaving the local development workflow.

## Why Kestrel Search?

* No search API key required
* DuckDuckGo, Bing, and Yahoo support
* Concurrent search and page retrieval
* Main-content extraction
* BM25 relevance ranking
* Clean JSON output for agents
* Agent skill support for Codex, Claude Code, and GitHub Copilot

## Quick example

```bash theme={null}
kestrelsearch search "python dataclasses"
```

For structured results:

```bash theme={null}
kestrelsearch search "python dataclasses" --output json
```

## Next steps

* [Install Kestrel Search](/installation)
* [Run your first searches](/quickstart)
* [Connect it to your coding agent](/guides/agent-integration)
* [Explore search options](/guides/search-options)

## Learn how it works

* [Search pipeline](/concepts/search-pipeline)
* [Ranking and result fairness](/concepts/ranking-and-fairness)
* [JSON output schema](/reference/output-schema)
* [Limitations](/reference/limitations)

## Project benchmark

In a small paired benchmark run on 28 August 2026, Kestrel's three-provider
fanout completed all 24 trials with answer quality close to native Web Search,
lower median latency, and fewer median model tokens. The suite contained eight
technical research tasks with three trials per task.

Read the [full results and limitations](/benchmarks). This project benchmark is
not a universal performance claim or a DeepSearchQA leaderboard score.