Local code intelligence MCP server and CLI for AI coding agents, providing semantic search and call graph analysis.
codanna is easy to set up with strong trust signals. Check agent compatibility and use-case fit before adding it to your workflow.
gh repo view bartolli/codanna --webOpen the official README and confirm the supported install method.
Add the server entry to your MCP client config.
Restart your agent and verify that the server tools appear.
Repository setup guidance
Strong trust signals; still review the README and permissions before production use.
Last commit was about 113 days ago.
687 GitHub stars indicate community interest.
7 open issues signal maintenance load.
Apache-2.0 license detected.
2 security/trust notes recorded.
Setup difficulty is 2/5.
Codebase intelligence layer for AI coding agents: code health, git analytics, dead code detection, and architectural decisions via MCP.
Deep code indexing MCP server for AI agents with hybrid FTS5 + embedding search, call graphs, and multi-repo workspaces.
A project template that turns your repository into stable infrastructure for AI-assisted development.
MCP server that gives AI coding assistants persistent memory, semantic code search, and live telemetry.
Codanna gives your AI coding assistant a deep understanding of your codebase. It can find functions by what they do, trace how code connects across files, and answer questions about your project instantly. It runs locally on your machine, so your code never leaves your computer.
Codanna is a local-first code intelligence tool that acts as an MCP (Model Context Protocol) server and CLI for AI coding agents. It provides structured knowledge of your codebase to AI assistants like Claude, Gemini, and Codex, enabling them to understand functions, trace relationships, and find implementations with surgical precision. Key features include semantic search (natural language queries against code and documentation), relationship tracking (call graphs, implementations, dependencies), document search (index markdown and text files for RAG workflows), and native MCP integration. It supports multiple languages including Rust, Python, JavaScript, TypeScript, Java, Kotlin, Go, PHP, C, C++, C#, Clojure, Lua, Swift, and GDScript. Performance is sub-10ms lookups with 75,000+ symbols/second parsing. Codanna is designed for rapid R&D and pair programming, providing instant answers when LSP is too slow. It requires approximately 150MB for the embedding model and runs on macOS, Linux, WSL, and Windows.
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Apache-2.0
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Local code intelligence MCP server and CLI for AI coding agents, providing semantic search and call graph analysis.
AI coding agent developers who want to give their agents deep code understanding., Software engineers using pair programming with AI assistants like Claude or Codex., R&D teams needing fast, local code intelligence for rapid prototyping and analysis.
The setup section provides repository-level starting guidance, not a guarantee of an independently verified installation. Check the official README and release notes.
Local code indexing may store source-derived metadata; keep indexes out of public artifacts. Embedding or semantic search setup should be reviewed for local data retention and model/provider boundaries.
Similar or complementary options to evaluate include repowise, srclight, attractor-guided-engineering-template.
Aug 20, 2026