What programming languages does CodeInteliMCP support?
It supports Python, JavaScript, TypeScript, Go, Rust, and more via Tree-sitter parsers.
@rahulvgmail
Basic information
Advanced MCP server for code intelligence with multi-repository support, Tree-sitter parsing, DuckDB graph database, and ChromaDB vector search
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"CodeInteliMCP": {
"command": "python",
"args": [
"setup_for_claude.py"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
CodeInteliMCP is an advanced MCP (Model Context Protocol) server that combines Tree-sitter parsing with graph databases and vector search for lightning-fast code intelligence across multiple repositories. It is designed for developers who need to analyze, search, and understand codebases through Claude or other MCP-compatible clients.
Clone the repository and run the automated setup script (python setup_for_claude.py), or install dependencies manually with pip and add the server configuration to your Claude Desktop config file. Use the provided MCP tools to add repositories, index code, and perform semantic or graph-based searches directly from Claude.
It supports Python, JavaScript, TypeScript, Go, Rust, and more via Tree-sitter parsers.
Graph relationships (e.g., function calls, imports) are stored in DuckDB, while semantic vectors are stored in ChromaDB.
Required Python packages include mcp, duckdb, chromadb, sentence-transformers, aiofiles, and tree-sitter with language-specific grammars.
You can index an entire repository or individual files with tools like `index_repository` and `index_file`. Auto-indexing provides smart incremental updates as code changes.
Initial indexing is under 1 minute for 100k lines of code, incremental updates under 1 second per file, usage queries under 50ms, and semantic search under 50ms.

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