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
Documentation
Visit chunkhound.github.io for complete guides:
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.jsonin 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
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