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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.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

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

Chunkhound

Install / Use

README