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.
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-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.
MCP server that gives AI coding agents persistent, semantic memory via Qdrant vector search, enabling workspace-aware codebase, documentation, and decision search.
