An advanced MCP server that provides deep code understanding and analysis using GraphRAG, AST parsing, and semantic memory, enabling AI agents to query and interact with complex codebases.
MCP server for semantic code search and explanation. Allows AI agents to search, ask questions, and manage memory about a codebase with local embeddings and LLM integration.
A local MCP server that parses codebases into semantic chunks, indexes them in SQLite with vector embeddings, and exposes MCP tools for LLM agents to query.
An MCP server that transforms codebases into intelligent, queryable knowledge bases, enabling AI assistants to perform semantic search, explore architecture, and analyze code relationships.
A lightweight MCP server that enables AI agents to perform deep codebase analysis by leveraging Gemini's massive context window for cross-file analysis and intelligent file selection.
A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.