An MCP server that enables LLMs to understand and work with TypeScript APIs they haven't been trained on by providing structured access to TypeScript type definitions and documentation.
A complete MCP server for Retrieval-Augmented Generation with file management and vector memory for agents. Supports multiple document formats (PDF, DOCX, TXT, MD, CSV, JSON) with semantic search using Hugging Face embeddings and ChromaDB for efficient vector storage.
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