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.

A tool designed for FIRST Robotics Competition teams, which can search multiple official document libraries such as WPILib, REV, and CTRE simultaneously, quickly obtain answers to programming and hardware configuration through natural language questions, and support VS Code integration and AI assistant optimization.

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 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.

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.

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 security-enhanced version of the NotebookLM MCP server that provides zero-hallucination answers, Gemini in-depth research, document API, and programmatic notebook creation functions, with 14 layers of enterprise-level security protection, including post-quantum encryption, certificate pinning, and compliance support.

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.

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

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.

The AI-assisted Insights Agent is an MCP agent that can transform natural language questions into accurate, interpretable, and reproducible data insights. It translates business questions into SQL queries through a natural language interface, provides interpretable results (including query statements, metric definitions, and data quality), and ensures the reproducibility of analysis. It aims to bridge the gap between business questions and data answers, improving the efficiency and transparency of data analysis.

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.

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.

A Hexo blog RAG MCP server based on vector search that transforms a personal blog into a dedicated knowledge base for AI assistants, enabling semantic retrieval and enhanced answers.

An MCP server that helps users with metacognition by saving questions in LLM learning sessions. It focuses on recording users' questions rather than AI answers, and tracks the learning journey and knowledge gaps in a lightweight way.

Hivemind is a multi - model AI consensus platform that can query GPT - 5.2, Claude Opus 4.5, and Gemini 3 Pro simultaneously and generate high - confidence comprehensive answers through a multi - round negotiation mechanism.

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.

Boundary MCP is a decision - structure analysis tool based on the MCP protocol. It doesn't provide answers or advice. Instead, it helps users see the essential structure of decision - making problems and what they're betting on by depersonalizing problems, identifying variables and constraints, generating the strategy space, analyzing risk distributions, and prompting cognitive biases, ultimately allowing users to take responsibility for their own choices.