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

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.

Yellhorn MCP is a model context protocol server that provides full codebase context support for code assistants by integrating the capabilities of Gemini and OpenAI, enabling development task planning, code review, and isolated environment creation.

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.

An MCP server based on Google's Gemini model, providing text-to-image generation and image transformation functions, supporting high-quality image generation, smart file name generation, and local storage.

This project is a proof-of-concept (POC) that demonstrates how to implement the Model Context Protocol (MCP) through a custom host for testing agentic systems. Core features include OpenAI-compatible API, Google Gemini integration, streaming response support, and tool invocation capabilities.

This is an MCP server project based on the OpenRouter API, providing network search functionality and using a specific Gemini model to return raw text results.

Implementation of the Gemini MCP Server, supporting interaction between Claude Desktop and the Google Gemini 2.5 Pro Experimental model

GemSuite MCP is the most comprehensive Gemini API integration server. It provides optimal performance, lowest token cost, and seamless integration through intelligent model selection, and supports various file processing and complex tasks.

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.

This project demonstrates how to use Google's Gemini 2.5 Pro model to interact with the flight search tool under the MCP protocol through the function call feature, enabling natural language queries for flight information and returning formatted results.

An MCP server integrated with the Gemini CLI tool, providing chat, content generation, and model list functions.

This project is a server for the Gemini model based on the MCP protocol, encapsulating Google's Gemini API and providing functions such as text generation, function calling, and file handling.

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.

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.

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.

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

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.

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.

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.

The Apktool MCP Server is an Android APK analysis service based on the Model Context Protocol. It integrates the Apktool tool and Gemini CLI artificial intelligence, providing functions such as APK decompilation, security analysis, privacy auditing, and reverse engineering guidance.

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.

GemSuite MCP is the most comprehensive Gemini API integration server, achieving optimal performance and lowest cost through intelligent model selection, supporting multi-file processing and complex task analysis.

An advanced reasoning and reflection tool based on the Gemini API, supporting multi - model integration and custom configuration

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.

A text-to-image generation MCP server based on the Gemini model

An MCP server implementation based on TypeScript that integrates the Gemini model by directly calling the Google Gemini API, supports the latest Gemini 2.0 Flash model, and maintains conversation context.

An MCP server based on TypeScript, integrating the Google Gemini Pro model

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.

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.

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.

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.

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 MCP server project that provides a service for automatically selecting the OpenAI O3 or Google Gemini 2.5 Pro model based on the number of tokens, supports recursive embedding of file paths in prompts, and is suitable for code review and solving complex problems.

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.

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.