This project sets up an MCP server for querying World Mini Apps documentation and integrating it with Cursor to help developers develop MiniApps more efficiently.

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.

A RAG system based on Python code analysis. It parses the code structure through AST and stores it in the Weaviate vector database, providing code query, natural language Q&A, and visualization functions, and supporting multi-codebase management and dependency analysis.

This project provides a set of toolkits for crawling website content and generating Markdown documents. At the same time, it realizes the semantic search function of documents through the MCP server and supports integration with tools such as Cursor.

brain - trust is an MCP server that connects the IDE with OpenAI through 3 simple tools, providing intelligent Q&A and structured plan review functions, supporting Docker deployment and integration with multiple IDEs

A Godot documentation query assistant based on Retrieval Augmented Generation (RAG), achieving intelligent Q&A through vectorization technology and semantic search.

An MCP server based on TypeScript that implements a Retrieval Augmented Generation (RAG) system for local documents, supporting querying and indexing of Git repositories and text files.

A Discord bot server integrated with the Mastra MCP component, providing intelligent Q&A, thread management, and command processing functions.

A server based on the Model Context Protocol (MCP) that provides Retrieval Augmented Generation (RAG) capabilities, integrates clients such as Cursor IDE and Claude Desktop, and enables domain knowledge Q&A, intelligent retrieval, and context-aware response generation.

An MCP server based on the LlamaIndexTS library, providing multiple LLM tool functions

This is an MCP document Q&A server based on the GroundX API that supports uploading documents and conducting intelligent Q&A on the document content.

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 document query MCP server based on the Gemini API, providing intelligent Q&A services for technical documents.

The project uses TypeScript and Node.js to develop an MCP server and integrates the LLM Studio API to optimize question answering, supporting dynamic prompt optimization

A custom MCP server that connects to the Dust.tt AI agent platform, realizing multi - cloud service integration through HTTP calls, providing systems thinking agent, RAG support, and web navigation capabilities.

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.

An MCP server that integrates the Perplexity AI search - enhanced language model with the Claude desktop, providing three tools of different complexity levels, suitable for quick queries, technical analysis, and in - depth research scenarios.

An intelligent learning assistance system based on PDF document analysis, providing functions such as document conversion, content organization, and question generation to help users learn efficiently.

A multi-chain gas price monitoring and intelligent recommendation dashboard based on Node.js and TailwindCSS, supporting the Ethereum, BNB, and Polygon networks, providing real-time gas price queries, natural language Q&A, and trading timing suggestions.

The Get Notes MCP Server provides intelligent knowledge base integration capabilities for AI assistants such as Claude through AI - enhanced knowledge base search and recall functions.

This project is a RAG (Retrieval Augmented Generation) service based on the AWS serverless architecture. It uses Lambda, OpenSearch Serverless, and S3 for document storage and retrieval, provides an MCP protocol interface through API Gateway, and integrates OpenAI for embedding and generation.

MaxKB is an open-source AI assistant designed specifically for enterprises. It supports the RAG process, workflow engine, and multimodal interaction, and is suitable for scenarios such as intelligent customer service and knowledge bases.