Discover Awesome MCP Servers

Extend your agent with 17,724 capabilities via MCP servers.

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IntelliPlan

IntelliPlan

IntelliPlan

Bitso MCP Server

Bitso MCP Server

Enables interaction with the Bitso cryptocurrency exchange API to access withdrawals and fundings data. Provides comprehensive tools for listing, filtering, and retrieving withdrawal and funding transactions with proper authentication and error handling.

mcp-server

mcp-server

Demo MCP

Zendesk MCP Server

Zendesk MCP Server

Enables AI agents to interact with Zendesk ticket data for customer support analysis and insights. It supports searching tickets by tags or keywords, retrieving ticket details, and analyzing agent performance and service trends.

Element-UI MCP Server

Element-UI MCP Server

Provides comprehensive Element-UI v2.15.14 component documentation including properties, events, and usage examples to help AI assistants generate accurate Vue 2 code.

Leantime MCP Server

Leantime MCP Server

Enables integration with Leantime project management software, allowing users to manage projects, tickets/tasks, time tracking, sprints, and goals through MCP-compatible tools and n8n workflows.

Asana MCP Server

Asana MCP Server

An MCP (Multi-Agent Conversation Protocol) server that enables interacting with the Asana API through natural language commands for task management, project organization, and team collaboration.

Golang Dev Tools

Golang Dev Tools

Golang Dev Tools

ikaliMCP Server

ikaliMCP Server

Provides a secure interface for AI assistants to interact with penetration testing tools like nmap, hydra, sqlmap, and nikto for educational cybersecurity purposes. Includes input sanitization and runs in a Docker container with Kali Linux tools for authorized testing scenarios.

Burp Suite MCP Server Extension

Burp Suite MCP Server Extension

MCP Server untuk Burp

GPT OpenMemory MCP Server

GPT OpenMemory MCP Server

Enables ChatGPT Desktop to save and manage conversation memories locally in SQLite, with features for searching past conversations, creating summaries, and exporting dialogues to markdown files.

Wiki OSRS MCP

Wiki OSRS MCP

Provides access to Old School RuneScape wiki information and game data through MCP tools. Enables users to query OSRS game content, items, and mechanics via natural language.

IOTA MCP Server

IOTA MCP Server

mcp-sse-server-demo

mcp-sse-server-demo

Demo server MCP SSE

USQL MCP Server

USQL MCP Server

Enables AI assistants to execute SQL queries against any database supported by the usql CLI tool. Provides seamless database interaction through MCP by forwarding queries directly to usql and returning results in JSON or CSV format.

Simple Streamable HTTP MCP Server

Simple Streamable HTTP MCP Server

A reference implementation demonstrating proper MCP server patterns with HTTP transport, featuring session management, progress notifications, and example tools for testing server functionality. Serves as a clean template for building MCP servers with streamable responses and comprehensive error handling.

trackio-mcp

trackio-mcp

An MCP server that enables AI agents to observe and interact with trackio experiment tracking, providing tools for managing ML experiments through natural language.

Google Search Console MCP Server

Google Search Console MCP Server

Connects Google Search Console with Claude AI to analyze SEO data through natural language, enabling search analytics reporting, URL inspection, indexing status checks, sitemap management, and data visualization for SEO professionals.

UniFi Network MCP Server

UniFi Network MCP Server

Enables AI assistants to manage UniFi network infrastructure through 50+ tools covering devices, clients, networks, WiFi, firewall rules, and guest access using the official UniFi Network API.

SQL MCP Server

SQL MCP Server

Enables read-only interaction with SQL databases through MCP, providing database metadata exploration, sample data retrieval, and secure query execution. Supports MySQL with multiple transport options and built-in security features including SQL injection protection and data sanitization.

zellij-mcp-server

zellij-mcp-server

Sebuah Server MCP melalui zellij melalui STDIO

Lunar Calendar Mcp

Lunar Calendar Mcp

Migadu MCP Server

Migadu MCP Server

Enables AI assistants to manage Migadu email hosting services through natural language, including creating mailboxes, setting up aliases, configuring autoresponders, and handling bulk operations efficiently.

Hello MCP Server

Hello MCP Server

mcp_server

mcp_server

Okay, here's a basic outline and example code snippets to guide you in implementing a sample MCP (Media Control Protocol) server using a Dolphin MCP client. This will be a simplified example to illustrate the core concepts. **Understanding the Components** * **MCP (Media Control Protocol):** A protocol for controlling media playback devices. It defines commands like play, pause, stop, seek, and volume control. * **Dolphin MCP Client:** A library or tool (presumably you have access to this) that acts as the client in the MCP communication. It sends commands to the MCP server. * **MCP Server:** The application you'll build. It listens for MCP commands from the Dolphin MCP client, interprets them, and then performs the corresponding actions (e.g., controlling a media player). **High-Level Steps** 1. **Choose a Programming Language and Framework:** Python is a good choice for its simplicity and networking libraries. You could use the `socket` module directly or a framework like `asyncio` for asynchronous handling. 2. **Set up a Socket Server:** Create a socket server that listens on a specific port (e.g., 5000). This server will accept connections from the Dolphin MCP client. 3. **Receive and Parse MCP Commands:** When a client connects, receive data from the socket. This data will be the MCP command. You'll need to parse the command string to determine the action to perform. 4. **Implement Command Handlers:** Create functions or methods to handle each MCP command (e.g., `handle_play()`, `handle_pause()`, `handle_seek()`). These handlers will interact with your media player (or a simulated media player for testing). 5. **Send Responses (Optional):** The MCP protocol may define response messages. You can send acknowledgements or status updates back to the client. 6. **Error Handling:** Implement error handling to gracefully deal with invalid commands, network issues, and other potential problems. **Python Example (using `socket` module)** ```python import socket import threading HOST = '127.0.0.1' # Loopback address (localhost) PORT = 5000 # Port to listen on # Simulated Media Player (replace with actual media player control) class MediaPlayer: def __init__(self): self.playing = False self.position = 0 # in seconds self.volume = 100 def play(self): print("Playing...") self.playing = True def pause(self): print("Pausing...") self.playing = False def stop(self): print("Stopping...") self.playing = False self.position = 0 def seek(self, position): print(f"Seeking to {position} seconds...") self.position = position def set_volume(self, volume): print(f"Setting volume to {volume}%") self.volume = volume media_player = MediaPlayer() # Create an instance of the media player def handle_client(conn, addr): print(f"Connected by {addr}") try: while True: data = conn.recv(1024) # Receive up to 1024 bytes if not data: break command = data.decode('utf-8').strip() # Decode and remove whitespace print(f"Received command: {command}") # Parse the command (very basic example) parts = command.split() action = parts[0].lower() if action == "play": media_player.play() conn.sendall(b"OK\n") # Send a simple acknowledgement elif action == "pause": media_player.pause() conn.sendall(b"OK\n") elif action == "stop": media_player.stop() conn.sendall(b"OK\n") elif action == "seek": try: position = int(parts[1]) media_player.seek(position) conn.sendall(b"OK\n") except (IndexError, ValueError): conn.sendall(b"ERROR: Invalid seek command\n") elif action == "volume": try: volume = int(parts[1]) media_player.set_volume(volume) conn.sendall(b"OK\n") except (IndexError, ValueError): conn.sendall(b"ERROR: Invalid volume command\n") else: print(f"Unknown command: {command}") conn.sendall(b"ERROR: Unknown command\n") except Exception as e: print(f"Error handling client: {e}") finally: conn.close() print(f"Connection closed with {addr}") def main(): with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((HOST, PORT)) s.listen() print(f"Listening on {HOST}:{PORT}") while True: conn, addr = s.accept() thread = threading.Thread(target=handle_client, args=(conn, addr)) thread.start() if __name__ == "__main__": main() ``` **Explanation:** 1. **Imports:** Imports the necessary modules (`socket` for networking, `threading` for handling multiple clients concurrently). 2. **Constants:** Defines the host and port for the server. 3. **`MediaPlayer` Class:** A simple class to simulate a media player. Replace the placeholder methods with actual media player control code (e.g., using a library like `vlc` or `pygame`). 4. **`handle_client(conn, addr)` Function:** * This function is executed in a separate thread for each client connection. * It receives data from the client using `conn.recv(1024)`. * It decodes the data (assuming UTF-8 encoding) and removes leading/trailing whitespace. * It parses the command string (very basic splitting on spaces). **Important:** A real MCP implementation would likely have a more robust parsing mechanism. * It calls the appropriate `media_player` methods based on the command. * It sends a simple "OK" or "ERROR" response back to the client. * It includes error handling to catch exceptions. * It closes the connection when the client disconnects or an error occurs. 5. **`main()` Function:** * Creates a socket object using `socket.socket(socket.AF_INET, socket.SOCK_STREAM)`. * Binds the socket to the specified host and port using `s.bind((HOST, PORT))`. * Starts listening for incoming connections using `s.listen()`. * Enters a loop that accepts incoming connections using `s.accept()`. * For each connection, it creates a new thread to handle the client using `threading.Thread(target=handle_client, args=(conn, addr))`. * Starts the thread using `thread.start()`. 6. **`if __name__ == "__main__":`:** Ensures that the `main()` function is only executed when the script is run directly (not when it's imported as a module). **How to Run:** 1. Save the code as a Python file (e.g., `mcp_server.py`). 2. Run the script from your terminal: `python mcp_server.py` 3. Use the Dolphin MCP client to connect to `127.0.0.1` on port `5000`. 4. Send MCP commands like "play", "pause", "stop", "seek 10", "volume 50". Observe the output in the server's terminal. **Important Considerations and Improvements:** * **MCP Protocol Specification:** You *must* have the full specification for the MCP protocol you're using. This example is a very simplified approximation. The specification will define the exact command formats, data types, and response codes. * **Robust Command Parsing:** Use a more robust parsing method (e.g., regular expressions, a dedicated parsing library) to handle complex command formats and arguments. * **Error Handling:** Implement comprehensive error handling to catch invalid commands, network errors, and other potential issues. Provide informative error messages to the client. * **Asynchronous I/O:** For a more scalable server, consider using `asyncio` for asynchronous I/O. This allows the server to handle multiple clients concurrently without using threads. * **Media Player Integration:** Replace the `MediaPlayer` class with actual code to control your media player. You might need to use a library specific to your media player (e.g., `vlc`, `pygame`, or a media player's API). * **Security:** If the MCP server will be exposed to a network, consider security implications and implement appropriate security measures (e.g., authentication, authorization, encryption). * **Threading vs. Asynchronous:** For a small number of clients, threading might be sufficient. For a larger number of clients, asynchronous I/O is generally more efficient. * **Dolphin MCP Client Documentation:** Refer to the Dolphin MCP client's documentation for details on how to connect to the server and send commands. **Example Commands from Dolphin MCP Client:** Assuming the Dolphin MCP client sends commands as simple text strings: * `PLAY` * `PAUSE` * `STOP` * `SEEK 60` (Seek to 60 seconds) * `VOLUME 75` (Set volume to 75%) **Indonesian Translation of Key Concepts:** * **MCP (Media Control Protocol):** Protokol Kontrol Media * **Dolphin MCP Client:** Klien Dolphin MCP * **MCP Server:** Server MCP * **Socket:** Soket * **Command:** Perintah * **Parse:** Mengurai (or Memproses) * **Handler:** Penangan * **Response:** Respon * **Error Handling:** Penanganan Kesalahan * **Media Player:** Pemutar Media * **Thread:** Utas (or Alur) * **Asynchronous I/O:** I/O Asinkron This detailed explanation and code example should give you a solid starting point for implementing your MCP server. Remember to adapt the code to your specific needs and the requirements of the Dolphin MCP client and the MCP protocol you're using. Good luck!

Zabbix MCP Server

Zabbix MCP Server

A middleware service that uses Model Context Protocol to analyze and automate Zabbix events with AI, enabling automated incident response and workflow automation through n8n integration.

MCP Weather Server

MCP Weather Server

Provides comprehensive weather information including current conditions, 7-day forecasts, and air quality data for any city worldwide using the Open-Meteo API. Features real-time weather data, hourly forecasts, sunrise/sunset times, and European Air Quality Index with human-readable descriptions.

OpenAPI to MCP

OpenAPI to MCP

Automatically converts any OpenAPI specification or Postman Collection into an MCP server, enabling AI assistants like Claude to directly interact with REST APIs without writing any code.

MCP-Server-MySSL

MCP-Server-MySSL

MySSL MCP Server

Elasticsearch MCP Server

Elasticsearch MCP Server

Connects to Elasticsearch databases using the Model Context Protocol, allowing users to query and interact with their Elasticsearch indices through natural language conversations.