X-ray vision for your agent.
Give your code assistant the ability to see through your codebase—understanding functions, tracing relationships, and finding implementations with surgical precision. Context-first coding. No grep-and-hope loops. No endless back-and-forth. Just smarter engineering in fewer keystrokes.
Built for rapid R&D and pair programming—instant answers when LSP is too slow. Learn more
Quick Start
Install (macOS, Linux, WSL)
curl -fsSL --proto '=https' --tlsv1.2 https://install.codanna.sh | sh
Or via Homebrew
brew install codanna
Or via Nix
nix run github:bartolli/codanna
Windows (PowerShell)
irm https://raw.githubusercontent.com/bartolli/codanna/main/scripts/install.ps1 | iex
See Installation Guide for Cargo and other options.
Initialize and index
codanna init
codanna index src
Search code
codanna mcp semantic_search_with_context query:"where do we handle errors" limit:3
Search documentation (RAG)
codanna documents add-collection docs ./docs
codanna documents index
codanna mcp search_documents query:"authentication flow"
What It Does
Your AI assistant gains structured knowledge of your code:
- "Where's this function called?" - Instant call graph, not grep results
- "Find authentication logic" - Semantic search matches intent, not just keywords
- "What breaks if I change this?" - Full dependency analysis across files
The difference: Codanna understands code structure. It knows parseConfig is a function that calls validateSchema, not just a string match.
Features
| Feature | Description |
|---|---|
| Semantic Search | Natural language queries against code and documentation. Finds functions by what they do, not just their names. |
| Relationship Tracking | Call graphs, implementations, and dependencies. Trace how code connects across files. |
| Document Search | Index markdown and text files for RAG workflows. Query project docs alongside code. |
| MCP Protocol | Native integration with Claude, Gemini, Codex, and other AI assistants. |
| Profiles | Package hooks, commands, and agents for different project types. |
Performance: Sub-10ms lookups, 75,000+ symbols/second parsing.
Languages: Rust, Python, JavaScript, TypeScript, Java, Kotlin, Go, PHP, C, C++, C#, Clojure, Lua, Swift, GDScript.
Integration
MCP protocol for AI assistants. Works with Claude Code, Cursor, Windsurf, and any MCP-compatible client. Supports stdio, HTTP, and HTTPS transports.
See Integration Guides for setup instructions.
Requirements
- ~150MB for embedding model (downloaded on first use)
- Build from source: Rust 1.85+, Linux needs
pkg-config libssl-dev - Windows support is experimental
Contributing
Contributions welcome. See CONTRIBUTING.md.
License
Apache License 2.0 - See LICENSE.
Attribution required. See NOTICE.
Built with Rust.