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.

This project builds a bridge between Claude Code and Google Gemini AI, enabling direct calls to Gemini in the Claude Code environment for Q&A, code review, and creative brainstorming, providing a convenient AI collaboration tool.

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

The Gemini Cloud Assist MCP server is a tool that connects MCP clients with the Google Cloud Gemini Cloud Assist API, allowing users to understand, manage, and troubleshoot Google Cloud environment issues using natural language.

An MCP image generation and editing server based on Google Gemini 2.5 Flash API, supporting text - to - image generation, image editing, iterative creation, and style transfer functions

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.

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.

An MCP server based on the Gemini API and Google Search, which provides intelligent answering functions for the latest information when used in conjunction with an AI assistant (such as Cline).

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.

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.

A code problem-solving service that combines various AI and community resources. By integrating the analyses of Gemini AI, Stack Overflow, and Perplexity AI, it provides developers with multi - perspective programming solutions.

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.

A thinking analysis server based on the Gemini API, providing the ability to decompose and think about complex problems

An automated test case generation tool that connects Jira and Gemini AI. It extracts requirement information from Jira through the MCP protocol, uses Gemini to intelligently generate test cases, and automatically creates them in Jira/Xray.

A local STDIO MCP server that provides tools for searching and retrieving Google Gemini API documentation, supporting full-text search and automatic content updates

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

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.

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.

A Blender MCP client application based on Firebase Genkit and Gemini, supporting the creation and manipulation of 3D scenes by selecting shapes, colors, textures, and scene descriptions, and enabling real-time interaction with Blender.

An AI planning system integrating Google Gemini CLI and Claude Code, providing functions such as automatic planning and execution, persistent context management, and MCP integration.

An asynchronous conversation AI service based on the Google Gemini API, which processes requests through a Redis queue and provides an MCP protocol-compatible API interface.

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.

A command - line code summarization tool based on Gemini Flash 2.0, supporting MCP server integration

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.

DeepRe is a Deno-based AI-driven CLI tool that automatically generates in-depth research reports using Google Gemini API. It supports multi-round iterative research and automatic evaluation, and outputs structured Markdown reports.

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

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.

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.

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 encapsulates MongoDB database operations as an AI tool through the MCP protocol, enabling interactive terminal operations between Gemini AI and MongoDB.

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.

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.

An MCP service for YouTube video analysis based on the Google Gemini Vision API, providing functions such as video description, summarization, Q&A, and key segment extraction.

A context management and caching MCP server based on Gemini, supporting a large context window of 2M tokens and providing session management and API caching functions.

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.