MCP server for semantic code search: index your codebase once, then search using natural language.
codebaxing is worth checking the docs before setup with strong trust signals. Check agent compatibility and use-case fit before adding it to your workflow.
gh repo view duysolo/codebaxing --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 163 days ago.
54 GitHub stars indicate community interest.
1 open issues signal maintenance load.
MIT license detected.
2 security/trust notes recorded.
Setup difficulty is 3/5.
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Codebaxing indexes your codebase and lets you search it using natural language, like asking a question. It understands the meaning behind your code, so you can find functions and logic even if you don't know the exact names. It works with AI editors like Claude and Cursor to help you navigate large projects quickly.
Codebaxing is an MCP (Model Context Protocol) server that provides semantic code search for your local codebase. It uses Tree-sitter to parse code into symbols, generates embeddings via a local or cloud model, and stores vectors in ChromaDB. Once indexed, you can search using natural language queries (e.g., "find authentication logic") and get relevant code snippets, even if the exact terms don't match. It supports multiple programming languages through Tree-sitter grammars. The tool offers a CLI for indexing and searching, and MCP tools for AI agents (search, stats, remember, recall, forget). Cloud embedding providers (Gemini, OpenAI, Voyage) are available for faster indexing. It integrates with Claude Desktop, Cursor, Windsurf, and other MCP-compatible editors.
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MCP server for semantic code search: index your codebase once, then search using natural language.
Full-stack developers working on large codebases who need fast code navigation., AI-assisted developers using Claude, Cursor, or Windsurf who want semantic search capabilities., Tech leads and architects who need to understand code structure across projects.
The setup section provides repository-level starting guidance, not a guarantee of an independently verified installation. Check the official README and release notes.
Indexing sends code to cloud embedding providers if configured (Gemini, OpenAI, Voyage). Ensure compliance with data policies. Local embedding runs entirely on your machine, but may be slow for large codebases.
Similar or complementary options to evaluate include metorial, mcp-context-forge, Microsoft Learn MCP Server.
Aug 20, 2026