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chunkhound

ChunkHound is a local-first codebase intelligence tool that uses the cAST algorithm and multi-hop semantic search to extract architecture patterns and institutional knowledge from code. It indexes over 30 languages locally to provide high-fidelity semantic and regex search results for complex repositories.

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361
Forks
35
Updated
Jan 8, 2026
Validated
Jan 9, 2026

ChunkHound

Local first codebase intelligence

Tests License: MIT 100% AI Generated Discord

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
  • 30 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, 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

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.

  1. Index your codebase
chunkhound index

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

Why ChunkHound?

ApproachCapabilityScaleMaintenance
Keyword SearchExact matchingFastNone
Traditional RAGSemantic searchScalesRe-index files
Knowledge GraphsRelationship queriesExpensiveContinuous sync
ChunkHoundSemantic + Regex + Code ResearchAutomaticIncremental + 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

Stop recreating code. Start with deep understanding.

License

MIT

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