Haiku RAG is an intelligent retrieval - augmented generation system built on LanceDB, Pydantic AI, and Docling. It supports hybrid search, re - ranking, Q&A agents, multi - agent research processes, and provides local - first document processing and MCP server integration.

This project builds a bridge between Claude Code and Google Gemini AI, enabling direct calls to Gemini in the Claude Code environment for Q&A, code review, and creative brainstorming, providing a convenient AI collaboration tool.

The Biel.ai MCP server connects the IDE to product documentation and enables AI tools to access and search the company's knowledge base through RAG technology, providing intelligent code completion and technical Q&A.

The MCP server of TiDB AI, providing a Q&A interface for Cursor

This project provides a guide for integrating AI chat functionality into Android Studio, enabling developers to interact with code and projects using natural language, including functions such as code Q&A, modification, explanation, and debugging.

An MCP server based on the Gemini API and Google Search, which provides intelligent answering functions for the latest information when used in conjunction with an AI assistant (such as Cline).

This project implements an MCP server based on the FAISS vector database, supporting the Retrieval Augmented Generation (RAG) function, including a complete workflow such as GitHub file download, document indexing, local query, and LLM integration.

File Context MCP is a TypeScript-based application that provides an API to query large language models (LLMs) through local file content. It supports multiple LLM providers (Ollama and Together.ai) and can process multiple file types to generate context-aware responses.

A Vercel AI SDK documentation query proxy service based on the MCP protocol, providing AI-driven document search and Q&A functions, and supporting integration with MCP clients such as Claude Desktop.

An MCP service that prevents AI hallucinations. When AI is uncertain, it can ask humans for help instead of being over - confident, improving development efficiency through a simple Q&A mechanism.

This project is an MCP server based on Google Cloud Vertex AI Gemini model, providing a rich toolset for code assistance and general Q&A, supporting web search-enhanced answers, document explanation generation, file system operations, and other functions.

An MCP service for YouTube video analysis based on the Google Gemini Vision API, providing functions such as video description, summarization, Q&A, and key segment extraction.

Flexible GraphRAG is a flexible platform that supports multi - data source document processing, automatic knowledge graph construction, hybrid search (full - text, vector, graph), and AI Q&A. It includes a FastAPI backend, an MCP server, and various front - end interfaces.

A server-side project based on the Model Context Protocol (MCP) that provides retrieval-augmented generation (RAG) capabilities. It can serve as a bridge between clients such as Cursor IDE and Claude Desktop and Contextual AI agents, enabling intelligent Q&A based on the knowledge base and context-aware responses.

A Q&A chatbot project about the EU AI Act, using a hybrid retrieval method (vector search + knowledge graph), providing local running and AWS Lambda deployment options.

List of Tablestore MCP server implementations, including Java and Python getting - started examples and a knowledge base Q&A system based on the MCP architecture, providing AI technical support.

A Pokémon Q&A assistant based on RAG technology, integrating the PokeAPI database and AI capabilities to provide accurate information interaction

An MCP server template based on the Bun runtime, specifically designed for building AI Q&A tools, providing interactive quiz functions with multiple categories and difficulty levels.

This is an MCP server for integrating the Get Notes API, providing functions for intelligent search and retrieval of information from the knowledge base, supporting multi-knowledge base management, and contributed by the Xiaoxibao public welfare community.

A Python-based chat workflow engine that integrates FastAPI, CLI, and Google ADK for unified AI Q&A processes and extended functionality

An AI-based food nutritional analysis assistant that identifies foods through images, calculates calorie and protein content, and supports nutritional knowledge Q&A and conversation memory functions.