A server that directly queries OpenAI models via the MCP protocol, supporting the o3 - mini and gpt - 4o - mini models, providing concise and detailed answers.

An MCP server implemented in Go language for obtaining the answers to the daily Wordle puzzles through the Wordle API. Supports two deployment methods: quick Docker deployment and local running.

The Multi-Model Advisor is a multi - model consulting server based on Ollama, which provides more comprehensive answers to questions by integrating the viewpoints of multiple AI models.

This project implements an MCP protocol server that provides a web search tool based on OpenRouter and can generate concise and real - time answers.

An MCP server that connects to the Wolfram Alpha API, providing a function similar to the '!wa' command in DuckDuckGo, and queries Wolfram Alpha through the API to get answers.

An AI-driven research orchestration service based on Cloudflare Workers that provides comprehensive and structured research answers by intelligently analyzing queries, invoking multiple professional tools in parallel, and integrating the results.

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.

This is an MCP+RAG proof-of-concept project for the oil and gas industry. It automatically distributes user queries to the correct domain services (such as drilling, production, procurement, etc.) through intelligent routing and combines hybrid retrieval technology to obtain accurate information from documents, providing answers with references to achieve fast and unified access to cross-domain data.

Cortex MCP is a model context protocol server that provides access to the Cortex API and uses workspace-related context to enhance the accuracy of question answers.

Gemini DeepSearch MCP is an automated research agent that uses the Google Gemini model and Google Search for in-depth multi-step web research and generates high-quality, referenced answers.

A tool that integrates the Perplexity AI API into Claude Desktop, supporting web search and providing answers with citations

An MCP server based on the Gemini API, providing AI - driven web search and summarization services, capable of synthesizing information and returning comprehensive answers with references.

The Multi-Model Advisor is a multi - model consulting system based on Ollama. It provides more comprehensive answers to questions by integrating different perspectives from multiple AI models. It uses the 'advisory board' model, allowing Claude to generate responses by synthesizing multiple AI perspectives.

Apple RAG MCP is a retrieval-augmented generation system that provides Apple development expertise for AI agents. It integrates official Swift documentation, design guides, and Apple Developer YouTube content, and provides accurate technical answers through AI-driven hybrid search technology.

Linkup for Claude is a tool that provides real-time Internet access capabilities for the AI assistant Claude, breaks through its knowledge cutoff limit, enables it to obtain the latest news, high-quality content, and trusted sources, and improves the timeliness and accuracy of answers.

Linkup for Claude is a plugin that provides real-time Internet access capabilities for the AI assistant Claude, breaking through the limit of its knowledge cutoff date, enabling it to obtain the latest news and high-quality content, and improving the accuracy and timeliness of answers.

An API service for querying the answers to the New York Times Connections game

This is a RAG assistant project designed for Pybricks beginners, focusing on providing retrieval and suggestions for official API documentation, tutorials, and code snippets. It is especially suitable for FLL students and coaches. The project includes document crawling, pre - processing, index building, and MCP tool services to ensure accurate answers and be beginner - friendly.