chunkhound

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

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

1. 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.

2. Index your codebase

chunkhound index

3. 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.

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