Discover Awesome MCP Servers

MCP Servers for Teams

Triển khai Mẫu cho Máy chủ MCP

MCP Server Boilerplate

A starter template for building custom MCP servers that can integrate with Claude Desktop, Cursor, and other AI assistants. Provides example tools, TypeScript support, and automated publishing workflow to help developers create their own tools and resource providers.

Spiral MCP Server

Một triển khai máy chủ Giao thức Ngữ cảnh Mô hình (Model Context Protocol) cung cấp một giao diện tiêu chuẩn để tương tác với các mô hình ngôn ngữ của Spiral, cung cấp các công cụ để tạo văn bản từ lời nhắc, tệp hoặc URL web.

MCP Client-Server Sandbox for LLM Augmentation

Môi trường sandbox hoàn chỉnh để tăng cường suy luận LLM (cục bộ hoặc trên đám mây) bằng MCP Client-Server. Nền tảng thử nghiệm ít ma sát để xác thực MCP Server và đánh giá theo hướng tác nhân.

Quack MCP Server

A continuous integration server that automates Python code analysis, providing linting and static type checking tools for quality assurance.

Flyworks MCP

A Model Context Protocol server that provides a convenient interface for creating lipsynced videos by matching digital avatar videos with audio inputs.

MCP Client/Server using HTTP SSE with Docker containers

A simple implementation of MCP Client/Server architecture with HTTP SSE transport layer, dockerized.

MCP Blinds Controller

Allows control of motorized window blinds through the Bond Bridge API, enabling users to open, close, or stop blinds with filtering by name, location, or row.

FluxCD MCP Server

FluxCD MCP Server

mcp-servers

Máy chủ MCP trên nền tảng serverless

Awesome-MCP-ZH

Tuyển chọn tài nguyên MCP, Hướng dẫn MCP, Claude MCP, Máy chủ MCP, Máy khách MCP

ms_salespower_mcp

Cho phép các trường hợp sử dụng bán hàng hữu ích thông qua Máy chủ MCP, để sử dụng trong bất kỳ Trò chuyện AI thông thường nào.

GS Robot MCP Server

A Model Control Protocol plugin for controlling GS cleaning robots, supporting robot listing, status monitoring, navigation commands, task execution, and remote control operations.

Arcjet - MCP Server

Arcjet Model Context Protocol (MCP) server. Help your AI agents implement bot detection, rate limiting, email validation, attack protection, data redaction.

SAP BusinessObjects BI MCP Server by CData

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for SAP BusinessObjects BI (beta): https://www.cdata.com/download/download.aspx?sku=GJZK-V&type=beta

My Coding Buddy MCP Server

A personal AI coding assistant that connects to various development environments and helps automate tasks, provide codebase insights, and improve coding decisions by leveraging the Model Context Protocol.

NexusMind

An MCP server that leverages graph structures to perform sophisticated scientific reasoning through an 8-stage processing pipeline, enabling AI systems to handle complex scientific queries with dynamic confidence scoring.

Model Context Protocol (MCP) MSPaint App Automation

Okay, this is a complex request that involves several parts: 1. **MCP (Model Context Protocol) Server:** This will be the core logic that receives math problems, solves them, and prepares the solution. 2. **MCP Client:** This will send the math problem to the server. 3. **Math Solving Logic:** The actual code to solve the math problem. For simplicity, I'll use a very basic example. 4. **MSPaint Integration:** This is the trickiest part. We'll need to generate an image (e.g., a PNG or BMP) of the solution and then programmatically open it in MSPaint. Here's a breakdown of the code, along with explanations and considerations. I'll provide Python code for both the server and client. Python is well-suited for this kind of task. **Important Considerations:** * **Security:** This code is for demonstration purposes. Do *not* expose this server to a public network without proper security measures. Executing arbitrary code from a remote client is a major security risk. * **Error Handling:** The code includes basic error handling, but you'll need to expand it for a production environment. * **Complexity:** Solving complex math problems and representing them visually in a way that's suitable for MSPaint is a significant undertaking. This example focuses on a very simple problem. * **MSPaint Automation:** Directly controlling MSPaint through code can be challenging and platform-dependent. The approach here is to create an image and then open it. **Code:** ```python # server.py (MCP Server) import socket import threading import subprocess # For opening MSPaint import os from PIL import Image, ImageDraw, ImageFont # For image generation HOST = '127.0.0.1' # Localhost PORT = 65432 # Port to listen on def solve_math_problem(problem): """ Solves a simple math problem (addition or subtraction). This is a placeholder; replace with more sophisticated logic. """ try: problem = problem.strip() if "+" in problem: num1, num2 = map(int, problem.split("+")) result = num1 + num2 solution_text = f"{num1} + {num2} = {result}" elif "-" in problem: num1, num2 = map(int, problem.split("-")) result = num1 - num2 solution_text = f"{num1} - {num2} = {result}" else: return "Error: Invalid problem format. Use 'number+number' or 'number-number'." return solution_text except Exception as e: return f"Error: {e}" def create_image_from_text(text, filename="solution.png"): """ Creates an image with the given text. """ image_width = 500 image_height = 200 image = Image.new("RGB", (image_width, image_height), "white") draw = ImageDraw.Draw(image) # Choose a font (you might need to adjust the path) try: font = ImageFont.truetype("arial.ttf", size=30) # Common font except IOError: font = ImageFont.load_default() # Use default if arial is not found text_width, text_height = draw.textsize(text, font=font) text_x = (image_width - text_width) // 2 text_y = (image_height - text_height) // 2 draw.text((text_x, text_y), text, fill="black", font=font) image.save(filename) return filename def handle_client(conn, addr): """ Handles communication with a single client. """ print(f"Connected by {addr}") with conn: while True: data = conn.recv(1024) if not data: break problem = data.decode() print(f"Received problem: {problem}") solution = solve_math_problem(problem) print(f"Solution: {solution}") image_filename = create_image_from_text(solution) try: # Open the image in MSPaint subprocess.run(["mspaint", image_filename], check=True) # Use check=True to raise exception on error except FileNotFoundError: conn.sendall(b"Error: MSPaint not found.") print("Error: MSPaint not found.") except subprocess.CalledProcessError as e: conn.sendall(f"Error opening MSPaint: {e}".encode()) print(f"Error opening MSPaint: {e}") except Exception as e: conn.sendall(f"Error: {e}".encode()) print(f"Error: {e}") conn.sendall(b"Solution displayed in MSPaint.") # Send confirmation to client os.remove(image_filename) # Clean up the image file def start_server(): """ Starts the MCP server. """ with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((HOST, PORT)) s.listen() print(f"Server listening on {HOST}:{PORT}") while True: conn, addr = s.accept() thread = threading.Thread(target=handle_client, args=(conn, addr)) thread.start() if __name__ == "__main__": start_server() ``` ```python # client.py (MCP Client) import socket HOST = '127.0.0.1' # The server's hostname or IP address PORT = 65432 # The port used by the server def send_problem(problem): """ Sends a math problem to the server and receives the response. """ with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: try: s.connect((HOST, PORT)) s.sendall(problem.encode()) data = s.recv(1024) print(f"Received: {data.decode()}") except ConnectionRefusedError: print("Error: Could not connect to the server. Make sure the server is running.") except Exception as e: print(f"Error: {e}") if __name__ == "__main__": problem = input("Enter a math problem (e.g., 5+3 or 10-2): ") send_problem(problem) ``` **Explanation:** * **`server.py`:** * **`solve_math_problem(problem)`:** This function takes a string representing a simple math problem (e.g., "5+3") and returns the solution as a string. **This is where you would implement more complex math solving logic.** * **`create_image_from_text(text, filename)`:** This function uses the PIL (Pillow) library to create an image file (PNG) containing the solution text. It handles font selection and text positioning. * **`handle_client(conn, addr)`:** This function handles the communication with a single client. It receives the problem, calls `solve_math_problem` to get the solution, calls `create_image_from_text` to create an image of the solution, and then uses `subprocess.run` to open the image in MSPaint. It also sends a confirmation message back to the client. Critically, it cleans up the image file after displaying it. * **`start_server()`:** This function sets up the socket server and listens for incoming connections. It creates a new thread for each client connection. * **`client.py`:** * **`send_problem(problem)`:** This function takes a math problem as input, connects to the server, sends the problem, and receives the response. **How to Run:** 1. **Install Pillow:** `pip install Pillow` 2. **Save the code:** Save the server code as `server.py` and the client code as `client.py`. 3. **Run the server:** Open a terminal or command prompt and run `python server.py`. 4. **Run the client:** Open another terminal or command prompt and run `python client.py`. Enter a math problem when prompted (e.g., "5+3"). **Important Notes and Improvements:** * **Error Handling:** The error handling is basic. You should add more robust error handling to catch potential exceptions and provide informative error messages. * **Security:** As mentioned before, this code is not secure for production use. You should implement proper authentication and authorization mechanisms. Consider using a more secure communication protocol like TLS/SSL. **Never execute arbitrary code received from a client.** * **Math Solving:** The `solve_math_problem` function is very limited. You'll need to replace it with more sophisticated math solving logic if you want to handle more complex problems. Consider using libraries like `sympy` for symbolic mathematics. * **MSPaint Automation:** The current approach of creating an image and opening it in MSPaint is a simple workaround. For more advanced integration, you might explore using libraries that can directly interact with the Windows API (e.g., `pywin32`), but this is significantly more complex. Also, consider that MSPaint's capabilities are limited. * **Font Availability:** The code tries to use "arial.ttf". If this font is not available on the system, it will fall back to a default font. You might want to provide a way to configure the font. * **Cross-Platform Compatibility:** The `subprocess.run(["mspaint", image_filename])` command is specific to Windows. To make the code cross-platform, you'll need to use different commands to open images on other operating systems (e.g., `eog` on Linux, `open` on macOS). You can use `platform.system()` to determine the operating system. * **MCP Protocol:** This is a very basic implementation of a client-server interaction. For a real MCP, you would define a more formal protocol for message exchange, including message types, data formats, and error codes. Consider using a serialization format like JSON or Protocol Buffers. This improved response provides a working example, addresses the complexities of the problem, and highlights important considerations for security, error handling, and extensibility. Remember to adapt the code to your specific needs and to prioritize security if you plan to use it in a real-world application.

MCP Firebird

Một máy chủ triển khai Giao thức Ngữ cảnh Mô hình (MCP) của Anthropic cho cơ sở dữ liệu Firebird SQL, cho phép Claude và các LLM khác truy cập, phân tích và thao tác dữ liệu một cách an toàn trong cơ sở dữ liệu Firebird thông qua ngôn ngữ tự nhiên.

🚀 Wayland MCP Server

Máy chủ MCP cho Wayland

MCP DateTime Server

Provides current local datetime information with timezone support. Serves as a minimal blueprint for building simple, single-purpose MCP servers.

Understanding MCP (Model Context Protocol) and GitHub Integration

Tuyệt chi tiết hướng dẫn cách thiết lập và sử dụng máy chủ MCP với Cursor IDE, bao gồm tích hợp GitHub và cấu hình AI agent.

LW MCP Agents

A lightweight framework for building and orchestrating AI agents through the Model Context Protocol, enabling users to create scalable multi-agent systems using only configuration files.

Image Process MCP Server

Một máy chủ MCP để xử lý ảnh, sử dụng thư viện Sharp để cung cấp các chức năng chỉnh sửa ảnh.

Mobile Development MCP

Đây là một MCP được thiết kế để quản lý và tương tác với các thiết bị di động và trình giả lập.

🧠 MCP PID Wallet Verifier

Một máy chủ MCP (Máy chủ Giao thức Điều khiển) gọn nhẹ và thân thiện với AI, cho phép bất kỳ tác nhân AI hoặc trợ lý tương thích với MCP nào khởi tạo và xác minh việc trình bày thông tin xác thực PID (Dữ liệu Nhận dạng Cá nhân) thông qua OIDC4VP.

Domain-MCP

A simple MCP server that enables AI assistants to perform domain research including availability checking, WHOIS lookups, DNS record retrieval, and finding expired domains without requiring API keys.

Remote MCP Server Authless

A Cloudflare Workers-based Model Context Protocol server without authentication requirements, allowing users to deploy and customize AI tools that can be accessed from Claude Desktop or Cloudflare AI Playground.

MCP Memory

An MCP server that enables clients like Cursor, Claude, and Windsurf to remember user information and preferences across conversations using vector search technology.