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.

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 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).

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.

Inkeep MCP is a universal document connector based on the Model Context Protocol (MCP). It connects local AI tools (such as Gemini CLI, Claude Desktop) with the "AI Q&A" function of any document website using the Inkeep service (such as Langfuse, Render, etc.) through browser simulation, allowing AI assistants to directly query official documentation.

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.

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.

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

MCP Vision Relay is an MCP server that provides image analysis capabilities for MCP clients that only support text, such as Claude and Codex, by encapsulating locally installed Gemini and Qwen command - line tools, enabling them to process pictures in local paths, URLs, or base64 - encoded format.

This is an MCP server project that allows users to define AI sub - agents for specific tasks (such as code review, test writing) in Markdown files and execute them in any MCP - compatible tool through the Cursor, Claude Code, or Gemini CLI backends, realizing the reuse of AI sub - agent workflows across IDEs.

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.

An MCP protocol server that allows Claude and Gemini CLI to perform automated trading interactions with multiple cryptocurrency exchanges through the Hummingbot API, supporting multi - server management and Docker deployment.

A server based on the Model Control Protocol (MCP) for managing and providing dynamic prompt templates. It utilizes the powerful Go text template engine, supports variables, conditions, loops, and reusable components, allows the creation of logic-driven prompt templates, and can seamlessly integrate with MCP-compatible clients such as Claude and Gemini.

The ZulipChat MCP Server is a protocol service that connects AI assistants to the Zulip chat platform. It supports multiple MCP clients such as Claude and Gemini, provides core functions such as message sending and receiving, search, and user management, and uses a two - tier tool architecture to optimize the AI experience.

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.

An MCP server based on Google Gemini AI that provides image, audio, and video recognition functions, supporting multiple transmission methods and client integration.

An AI vision analysis MCP server based on Google Gemini and Vertex AI, supporting multimodal analysis of images and videos, providing functions such as object detection and image comparison, and can be integrated into various MCP clients.

Gemini Bridge is a lightweight MCP server that connects AI programming assistants to Google Gemini AI through the official CLI, supporting multi - client interaction without API costs.

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.

The Gemini CLI Orchestrator is a multi-step code analysis tool based on Google Gemini AI. It guides developers through a systematic analysis via a structured workflow rather than replacing human thinking. It offers four core functions: analysis planning, prompt optimization, iterative analysis, and result synthesis, and is suitable for complex scenarios such as security audits and performance optimization.

A tool for interacting with globally published books through the MCP client, supporting long - text pagination and caching, and planning to integrate Gemini Q&A and Sci - Hub resources.

The combination of Gemini CLI and the MCP server built with Google Apps Script extends the automation capabilities of Google Workspace through a low - code platform, providing support for 41 tools covering services such as Gmail, Drive, Calendar, etc., and enabling multi - step execution of complex tasks.

This project implements an MCP server based on the Gemini API, providing access to various technical documents. With a large context window of 2M tokens, it directly processes complete documents without the need for chunking or retrieval steps of traditional RAG systems. It supports functions such as document query, code specification check, and problem - solving hints, and is suitable for the Roo/Cline environment.

SuperAgent is an MCP server that uniformly calls the Codex, Gemini, and Continue CLI agents. It supports parallel task execution, manages preset system prompts, and provides structured tool calls to clients through the MCP protocol.

An MCP server that provides FAF - format project context understanding for the Gemini CLI. Automatically capture the project technology stack, goals, and quality standards through the .faf file, enabling AI to fully understand the project without repeated inquiries.

This is a patched Gemini MCP tool that allows AI assistants to interact with Google Gemini through the Gemini CLI, which is particularly suitable for large file analysis and codebase processing and supports the Windows system.

DeepRe is a Deno-based CLI tool that automatically generates in-depth research reports using the Google Gemini API, supporting Japanese and Markdown output.

Polydev is a multi - model AI programming assistant that simultaneously calls multiple cutting - edge AI models such as GPT - 5, Claude, Gemini, and Grok through a single MCP server, providing a comprehensive perspective for developers' programming agents. It supports one - click installation and can be integrated into mainstream IDEs such as Claude Code and Cursor, significantly improving the code problem resolution rate and reducing costs.

An MCP server implementation based on Gemini, providing powerful context management and caching functions, supporting a context window of up to 2 million tokens, and suitable for integration with various AI clients.

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.

A command-line interface enhancement tool that provides an enhanced CLI for interacting with the Gemini API, supporting local command execution and interactive program automation

The code review MCP server based on Gemini CLI provides structured code review functions for AI assistants by automatically collecting local code differences and static analysis results.

A working demonstration project of the Model Context Protocol (MCP) integrated with Google Gemini, including configuration and operation guides for the server and client.

A lightweight, stateless MCP server that allows development agents (such as Claude Code and GitHub Copilot) to delegate in - depth codebase analysis tasks to the Gemini CLI. By reading files locally and returning structured JSON results, it reduces the context consumption and model usage of agents.

Project for integrating Gemini AI into MCP client and server

Gemini Rust Suite is a Rust-based Google Gemini model interaction tool suite that provides a CLI interface, tool call protocol (MCP), persistent semantic memory, and other functions, supporting integration with external services.

A modern to-do list application based on FastAPI and the MCP protocol, supporting complete CRUD operations, task statistics, and integrating with the Gemini CLI through the FastMCP server to achieve natural language task management.

The Windows-compatible version of the Gemini MCP tool, which fixes cross-terminal compatibility and response format issues, and supports AI assistants to interact with Google Gemini CLI via the MCP protocol

Moonbridge is an MCP server that allows multiple AI coding agents (supporting backends such as Kimi, Codex, OpenCode, Gemini) to be generated in parallel from MCP clients such as Claude Code and Cursor, used to try multiple code solutions simultaneously, enabling parallel exploration and task execution at a lower cost.