ChunkHound

Local code search and research with citations: semantic search, cross-file behavior explanation and git-history queries

CLI

Medium risk

We rate an entry medium when the tool runs code, makes network calls or reads project files. Check what exactly it does before installing.

Why this level

  • Reads and indexes code files
  • May send code to an external provider for semantic search
All reasons and checks

chunkhound/chunkhound

Install

In your terminal, with SkillFoxx CLI

npx skillfoxx add cli/chunkhound

Detects the agents on your machine, checks the risk and pins the version.

Other ways to install

Install the tool

pipx install chunkhound

Without pipx, pip install chunkhound works too.

You will need: pipx

Checked against the repository on Sep 25, 2026, commit d794723.

Text for your agent

Install: uv tool install chunkhound, then chunkhound index . and chunkhound research "question". For semantic search set an embedding provider in .chunkhound.json.

Other ways from the author
uv tool install chunkhound

After installing, run chunkhound index . in the project directory.

This is third-party code. Review the repository files before installing.

What it does

ChunkHound indexes a codebase and lets you search it by meaning, not only by text. It explains behavior across several files with source citations and can answer questions about git history: by last commits, tag, branch or range. Indexing is local and stays under your control. Regex search works without external services, while semantic search and deep research need an embedding provider and a model.

Who it is for. For developers who need semantic search and analysis of a large or unfamiliar codebase.

Good fit when

  • You need to find code by meaning rather than exact text
  • You need behavior explained with file citations
  • You need to understand a large PR from git history

Not a fit when

  • Plain text search over the project is enough
  • You cannot send code to an external embedding provider

Example request

Index the project with ChunkHound and explain, with citations, how authentication works

Limitations

Semantic search and deep research need an embedding provider and a model, some of them paid, while regex search works without them. The index has to be built, which takes time on a large codebase. You can choose local providers to keep code from leaving the machine.

How to disable. Remove the tool with uv tool uninstall chunkhound and delete the created index.

Security check

  • Reads and indexes code files
  • May send code to an external provider for semantic search

README in short

The README describes ChunkHound as a local code search and research tool with source citations. Installation is via uv, and the index and research commands build an index and give grounded answers. Regex search works without a provider, while semantic search and deep research need an embedding provider and a model set in .chunkhound.json. Many languages and git-history search are supported.

FAQ

Can it run without external services?

Regex search works locally without a provider. Semantic search and research need an embedding provider and a model, and you can pick local ones.

Does git-history search work?

Yes, you can ask by last commits, hash, tag, branch or range.

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Foxx AIChunkHound

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