This project implements an MCP server for interacting with the Wolfram Alpha API, enabling chat applications to perform calculation queries and obtain structured knowledge. It includes an MCP client example based on Gemini, demonstrating how to connect a large - language model to the MCP server for real - time interaction with the Wolfram Alpha knowledge engine.

An MCP server that combines Claude Code and Google Gemini AI to achieve in - depth code analysis through multi - model collaboration. Claude is good at local context operations and CLI workflows, while Gemini uses its ultra - large context window for distributed system debugging and long - trace analysis.

A multi-agent deep research system based on MCP, integrating LinkUp search, CrewAI coordination, and the Gemini large model, providing an interactive interface through Streamlit.

OmniLLM is an MCP server that serves as a bridge between Claude and other large language models (such as ChatGPT, Azure OpenAI, and Google Gemini), providing a unified AI access interface.

An AI research assistant tool based on Node.js and the Gemini API. It uses Firecrawl for web data scraping, leverages the Gemini large - model for in - depth language understanding and report generation, supports iterative in - depth research, and can be integrated with the MCP protocol.

DeepView MCP is a code analysis service based on the Gemini large model, providing IDEs with the ability to understand the context of the entire codebase.

A RAG system built with open-source embedding models, vector databases, and the Gemini large language model, supporting local document processing and dynamic index update.

A web - based dialogue agent based on multiple large language models (such as Google Gemini, Anthropic Claude, etc.), which implements multi - step tool execution through the Vercel AI SDK and can interact with external services (such as WhatsApp, GitHub, etc.).