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 enables LLM clients like Claude to perform semantic code search and answer questions about a codebase using tree-sitter parsing and sqlite-vec vector storage.
MCP server for semantic code indexing using vector embeddings, enabling AI agents to maintain persistent memory of codebases through natural language queries and intelligent chunking.
A local MCP server that provides AI coding assistants with semantic search capabilities over codebases. It indexes code using local embeddings and exposes tools for efficient code retrieval, saving tokens and improving response quality.
Local MCP server that provides semantic search (RAG) over code repositories, enabling AI clients like Claude and Gemini to access project context without manual re-upload.
A local-first MCP server that provides AI agents with safe codebase access through file discovery, hybrid lexical-semantic search, and project introspection. It features durable local memory and semantic indexing while keeping all data and processing entirely on your local machine.