Integrates Google's Gemini AI models with MCP-compatible clients like Claude Desktop, enabling access to advanced AI capabilities.
Accelerates LLM agent workflows by providing high-performance Go tools and native MCP servers for optimized file operations, search, and context management.
Enables Gemini and Doubao users to effortlessly remove image watermarks and download conversation content with a simple Tampermonkey script.
Provides a robust PowerShell interface for configuring, enabling, and disabling Model Context Protocol (MCP) servers within the Gemini CLI environment.
Provides AI assistants with direct access to comprehensive Gemini API documentation.
Provides a Model Context Protocol (MCP) server for seamless integration with Gemini's AI models.
Provides a comprehensive toolkit unifying 50+ free tools, a built-in RAG system, and a GUI, all designed to run out-of-the-box with various LLM clients.
Provides a practical example for developing Gemini CLI extensions.
Establishes a self-hosted Model Context Protocol server for AI memory, utilizing PostgreSQL with pgvector for efficient data storage and retrieval.
Enables AI-powered image processing through a Gemini 2.5 Flash-based MCP server.
Provides a foundational template for building custom Model Context Protocol (MCP) servers to integrate with various AI assistants.
Extends Gemini CLI with an Ollama-powered MCP server, featuring prompt optimization, speculative decoding, and self-correction for enhanced AI interactions.
Provides a sandbox environment for testing the `fastmcp` Python library.
Validates AI responses using project context and Gemini, acting as a middleware bridge between Cursor IDE and AI models.
Build and deploy AI agents easily using a flexible, modular framework for seamless integration and control.
Converts hexadecimal color codes to their closest matching CSS color names.
Offload deep codebase analysis to Gemini CLI, enabling AI agents to utilize Gemini's free tier and optimize their own context and model usage.
Provides a clean foundation for creating custom Model Context Protocol (MCP) servers to integrate with various AI assistants.
Empowers LLM agents to integrate and utilize the Gemini CLI and other developer tools via a standardized JSON-RPC interface.
Provides a foundational example for integrating custom tools with the Gemini CLI using the Model Context Protocol (MCP).
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