Zen MCP is a multi-model AI collaborative development server that provides enhanced workflow tools and cross-model context management for AI coding assistants such as Claude and Gemini CLI. It supports seamless collaboration of multiple AI models to complete development tasks such as code review, debugging, and refactoring, and can maintain the continuation of conversation context between different workflows.

An MCP server project that enables interaction between Claude Desktop and Google Gemini AI models

LOTUS-MCP is an open-source model coordination protocol that integrates the two major AI models, Mistral and Gemini, providing a unified interface, context sharing, and tool integration to achieve intelligent routing and cost optimization.

Kontxt MCP Server is a codebase context analysis service based on the Gemini model, providing codebase understanding tools for AI clients and supporting multiple transport protocols and context attachment functions.

The Gemini MCP Server is a middleware designed for the Claude desktop application, enabling image generation through Google's Gemini AI model. This project provides a convenient installation and configuration wizard, supports Docker containerized deployment, and allows users to customize generation parameters.

The LangExtract MCP Server is a FastMCP - based server that extracts structured information from unstructured text through the Google Gemini model, providing text information extraction capabilities for AI assistants such as Claude Code and supporting smart caching and persistent connections.

A chat platform integrating LangChain, a custom MCP server, and Google Gemini AI model, providing enhanced conversation functions.

GemForge is an enterprise-level tool that connects Google Gemini AI with the MCP ecosystem. It provides functions such as real-time web access, advanced reasoning, code analysis, and multi-file processing. It supports more than 60 file formats and has intelligent model selection and a powerful error handling 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.

A data analysis and research MCP server based on the Gemini Flash 2 AI model, providing functions such as data parsing, intelligent analysis, report generation, and automatic email sending.

The AI Studio MCP Server is a model context protocol server integrated with Google AI Studio/Gemini API, providing content generation functions that support files, conversation history, and system prompts.

A data analysis and research MCP server based on the Gemini Flash 2 AI model, providing functions such as data parsing, statistical analysis, research report generation, and automatic email sending.

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 basic MCP application that combines a FastAPI backend and a Gradio frontend, supporting interaction with AI models through a simple interface and integrating the Google Gemini API to implement paper search and analysis functions.

A modern MCP server implementation that provides web search and research paper analysis functions for AI assistants through the Brave Search API and Google's Gemini model.

An MCP server that allows Claude Code to consult more powerful AI models (such as o3, Gemini 2.5 Pro, DeepSeek Reasoner) when in need of in - depth analysis of complex problems.

An MCP server based on Google Gemini's image generation model that allows AI agents to generate, edit, and describe images through text prompts, supporting multiple models and configuration options.

MCP Toolz is an MCP server tool for Claude Code that supports cross-session context and to-do list saving and can obtain feedback from multiple AI models such as ChatGPT, Claude, Gemini, and DeepSeek.

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.

OmniMind is an open - source Python library designed to simplify Model Context Protocol (MCP) integration and support the development of AI agents, workflows, and automation. It offers plug - and - play functionality, has built - in multiple tools, and provides intelligent responses based on Google Gemini, making it suitable for developers and beginners to quickly build AI applications.

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.

Ultra MCP is a multi-model AI protocol server that integrates AI models such as OpenAI and Gemini through a unified MCP interface, providing support for Claude Code and Cursor. It features zero-configuration installation, a built-in usage analysis dashboard, and a modern web interface.

An MCP server for multi - AI agent consultation that integrates different AI models such as OpenAI, Anthropic, and Google Gemini to provide multi - model perspective support for code analysis and problem - solving.

LLM Gateway is a server based on the MCP protocol that supports advanced AI agents (such as Claude 3.7) to intelligently delegate tasks to lower - cost LLM models (such as Gemini Flash), achieving cost optimization and performance balance.

This project implements a full-stack AI agent system inspired by the model context protocol, including a React front-end and a FastAPI back-end. The back-end serves as an AI coordinator, using Google Gemini to parse natural language instructions, safely call the file system, browser, or GitHub tools to perform tasks, and return the structured results to the front-end. The system focuses on software development scenarios, providing secure sandbox file operations, real-time web browsing, and repository inspection functions, and visualizing the tool call process.

Second Opinion MCP is a multi - AI model consulting platform that allows users to instantly obtain second opinions from different AI models such as OpenAI, Gemini, Grok, Claude, HuggingFace, DeepSeek, and OpenRouter in Claude conversations, supporting functions such as code comparison, creative writing, problem - solving, and cross - model analysis.

This project is an MCP server used to integrate Google's Gemini model with Claude Code to achieve collaboration between the two AI systems. It provides functions such as direct query, collaborative brainstorming, code analysis, text analysis, content summarization, and image prompt generation.

This project is a server that implements the Model Context Protocol (MCP) specification. It serves as a bridge for MCP clients (such as Claude Desktop) to interact with Google's Gemini AI models through a standardized interface. It supports multiple Gemini models and function calls, provides tools such as single - question asking, multi - round conversations, and function calls, and can be deployed locally or via Docker.

This project uses advanced AI prompting techniques to enable an AI agent (based on Google Gemini model) to interact with the legacy Windows application MSPaint through the Model Context Protocol (MCP) to solve complex math problems and draw solutions on the canvas.

MCP Server is a middleware server that serves as a bridge between the Cursor IDE and AI models, validating AI responses using project context and Gemini.

The Twitch MCP server is an AI toolset provided for Twitch streamers. It connects chat assistants (such as Gemini CLI, Qwen Coder, Claude Code, etc.) to Twitch chat through the Model Context Protocol (MCP) to implement chat management, content moderation, and audience interaction functions.

An MCP server that provides browser automation capabilities for AI models, enabling models such as Claude and Gemini to perform web browsing, searching, and interaction operations through natural language instructions.

A data analysis and research MCP server based on the Gemini Flash 2 AI model, providing data parsing, AI analysis, visualization reporting, and automated email sending functions

This project uses the Model Context Protocol (MCP) framework to achieve automated control of the Windows Paint program (MSPaint) by an AI agent. It uses pywinauto to operate the Paint tool and combines with the Gemini model to implement drawing functions driven by natural language instructions.

MCPHubs is a website built on Next.js to showcase open - source projects related to Anthropic's Model Context Protocol (MCP). It obtains project information through the GitHub API and uses Google Gemini Pro model for AI analysis to evaluate the relevance of projects to MCP, providing project list, detail display, and README rendering functions.

This project is a tutorial for building a Model Context Protocol (MCP) server based on Google's Gemini 2.0 model. It includes a complete code implementation, demonstrating how to enable AI models to seamlessly access external tools (such as the Brave Search API) through the MCP standard, and provides an example of a flexible architecture design.

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.).

The Gemini MCP Server project implements the Model Context Protocol (MCP) service, enabling Claude Desktop to interact with Google's Gemini AI model. It provides full MCP protocol support, real - time response streaming, secure API key handling, and configurable model parameters, and is implemented in TypeScript.