ChunkHound

Local-first codebase intelligence

Your AI assistant searches code but doesn't understand it. ChunkHound researches your codebase—extracting architecture, patterns, and institutional knowledge at any scale. Integrates via MCP.

Features

• cAST Algorithm - Research-backed semantic code chunking

• Multi-Hop Semantic Search - Discovers interconnected code relationships beyond direct matches

• Semantic search - Natural language queries like "find authentication code"

• Regex search - Pattern matching without API keys

• Local-first - Your code stays on your machine

• 32 languages with structured parsing

• Programming (via Tree-sitter): Python, JavaScript, TypeScript, JSX, TSX, Java, Kotlin, Groovy, C, C++, C#, Go, Rust, Haskell, Swift, Bash, MATLAB, Makefile, Objective-C, PHP, Dart, Lua, Vue, Svelte, Zig

• Configuration: JSON, YAML, TOML, HCL, Markdown

• Text-based (custom parsers): Text files, PDF

• MCP integration - Works with Claude, VS Code, Cursor, Windsurf, Zed, etc

• Real-time indexing - Automatic file watching, smart diffs, seamless branch switching, and explicit backend selection (watchdog, watchman, polling)

Documentation

Visit chunkhound.ai for documentation:

• Configuration Guide

Why ChunkHound?

Approach Capability Scale Maintenance Keyword Search Exact matching Fast None Traditional RAG Semantic search Scales Re-index files Knowledge Graphs Relationship queries Expensive Continuous sync ChunkHound Semantic + Regex + Code Research Automatic Incremental + realtime

Ideal for:

• Large monorepos with cross-team dependencies

• Security-sensitive codebases (local-only, no cloud)

• Multi-language projects needing consistent search

• Offline/air-gapped development environments

License

MIT

Requirements

• Python 3.10+

• uv package manager

• API keys (optional - regex search works without any keys)

• Embeddings: VoyageAI (recommended) | OpenAI | Local with Ollama

• LLM (for Code Research): Claude Code CLI or Codex CLI (no API key needed) | Anthropic | OpenAI | Grok (xAI)

Installation

# Install uv if needed
curl -LsSf https://astral.sh/uv/install.sh | sh

# Install ChunkHound
uv tool install chunkhound

Quick Start

• Create .chunkhound.json in project root

{
 "embedding": {
 "provider": "voyageai",
 "api_key": "your-voyageai-key"
 },
 "llm": {
 "provider": "claude-code-cli"
 }
}

Note: Use "codex-cli" instead if you prefer Codex. Both work equally well and require no API key.

• Index your codebase

chunkhound index

• Search changed code in recent commits

# Last N commits
chunkhound search "authentication changes" --last-n 20

# Changes introduced by that commit (diff against its parent; root commits use empty tree)
chunkhound search "database migration" --commit-hash abc1234

# Custom git range
chunkhound search "API changes" --commit-range v2.0..HEAD

# Deep research over recent changes
chunkhound research "what changed in the auth module?" --last-n 50

--vector-source controls scope: diff (default, changed code only), both (merges diff + DB), db (ignore diff).

For configuration, IDE setup, and advanced usage, see the documentation.