A Dockerized MCP server that fetches your GitHub repositories, indexes them into a local vector database, and exposes semantic code search tools to LLM clients for tailored technical mock interviews grounded in your actual code.
An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
Uses Ollama or OpenAI to generate embeddings.
Docker files included
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.
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.
