This is an automated deployment script project for installing and configuring multiple Model Context Protocol (MCP) robot services on a Windows system, including functions such as file system, GitHub, search, and memory management, and provides detailed installation guides and troubleshooting methods.

An MCP server implementation for the Deepseek R1 language model based on Node.js, supporting an 8192-token context window, providing stable Claude Desktop integration and model parameter configuration.

A high - performance MCP server that provides an efficient knowledge interface between LLMs and MongoDB, supporting small context window optimization and multiple domain data models.

A server implementation based on the Model Context Protocol (MCP) for executing CMD commands and SSH connections on Windows and Linux systems, supporting the integration of command - line operations through MCP - compatible applications.

An MCP server for extending the context window/memory of AI agents, supporting the storage, retrieval, and management of memory content, including semantic search functionality.

An MCP server that provides intelligent text summarization functions for AI agents, optimizing context window management and improving AI work efficiency

MCPControl is a Windows system control server that provides programmatic control of system operations such as mouse, keyboard, window management, and screen capture through the Model Context Protocol.

An MCP server for expanding the context window/memory of AI agents, supporting storage, retrieval, and management of memories, including semantic search functionality.

The Screeny MCP Server is a privacy-first screenshot service designed specifically for macOS, allowing AI agents to securely capture screenshots of pre-approved application windows and providing a visual context for development and debugging tasks.

dap-mcp is a Debug Adapter Protocol (DAP) implementation based on the Model Context Protocol (MCP), aiming to optimize and extend the context window of large language models to enhance the debugging workflow.

The MindManager MCP Server is a service implementation based on the Model Context Protocol (MCP), providing a standardized interface for the `mindm` library to interact with MindManager on Windows and macOS. It allows for the programmatic operation of elements such as mind map documents, topics, and relationships through the MCP protocol and supports exporting mind maps to multiple formats for use by LLMs.

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.

An MCP server integrated with an AI code editor that optimizes Cursor's proxy capabilities through the million - token context window of Gemini 2.5 and task management features.

CMD MCP Server is a server implementation based on the Model Context Protocol (MCP), which supports executing CMD commands and SSH connections on Windows and Linux systems, allowing the integration of command - line operations with MCP - compatible applications.

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 TypeScript-based MCP server that implements an LLM query system, supporting task delegation and context window offloading.

MCP Analyst is an MCP server that enables Claude to analyze local CSV or Parquet files, suitable for scenarios involving large datasets that exceed the context window limit or require cost optimization.

MCPControl is a Windows system control server that provides programming control for system operations such as mouse, keyboard, window management, and screen capture through the Model Context Protocol.

An intelligent text summarization MCP server designed for AI workflows, providing intelligent summarization functions for command output, file content, and directory structure, and optimizing the context window management of AI agents.

Alpha Vantage MCP is a Model Context Protocol server that provides access to stock and financial data. It integrates all the functions of Alpha Vantage API endpoints and reduces the use of the context window through optimized endpoint organization.

Claude Crew is a tool for creating autonomous coding agents, focusing on maximizing cost - effectiveness through efficient use of the context window, prioritizing operation verification through unit tests, and providing project - optimized MCP and context information.

dap-mcp is a DAP session management tool based on the MCP protocol, aiming to optimize and expand the context window of large language models and improve the debugging workflow.

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.

Photoshop MCP Server is a service that integrates with Adobe Photoshop through the Model Context Protocol (MCP), allowing AI assistants and other MCP clients to programmatically control Photoshop. It provides functions such as creating, opening, and saving documents, operating on layers, and retrieving session information, and only supports the Windows system.

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.

An MCP server based on Redis and in-memory caching, used to optimize and manage the context window of large chat histories, supporting intelligent summarization, dual caching layers, and API compatibility.

MCP Linker is a convenient tool that helps users add Model Context Protocol servers to supported clients (such as Claude, Cursor, etc.) with one click and supports the macOS and Windows systems.

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.

The Temp Notes MCP Server is a temporary information storage service designed for AI agents, supporting cross - conversation and context - based storage and retrieval of temporary notes to help solve the context window limitation problem in complex tasks.

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.

MCPControl is a Windows control server that enables programmatic control of system operations through the Model Context Protocol, including mouse and keyboard control, window management, and screen capture. It provides a bridge for AI models to interact with the desktop.

The Hyprland MCP Server is an unofficial, lightweight server that exposes the functionality of the Hyprland window manager to language models through the Model Context Protocol (MCP), supporting natural language queries and control of Hyprland's window management, layout, input, etc.