Discover Awesome MCP Servers

PostgreSQL MCP Server

Un servidor de Protocolo de Contexto de Modelo que proporciona acceso de solo lectura a bases de datos PostgreSQL, permitiendo a los LLM inspeccionar esquemas de bases de datos y ejecutar consultas de solo lectura.

MCP-RAG

An MCP-compatible system that handles large files (up to 200MB) with intelligent chunking and multi-format document support for advanced retrieval-augmented generation.

Logo-Analyze

An MCP server for intelligent logo extraction and processing, supporting automatic recognition and extraction of logo icons from website URLs, and providing image processing and vector conversion functions.

MCP Secure Installer

Automatically installs and containerizes MCP servers from GitHub repositories using MCP sampling to analyze repositories and create appropriate Docker images.

Jenkins MCP Server

Enables AI assistants to interact with Jenkins CI/CD systems for build management, job monitoring, console log analysis, and debugging through natural language commands.

MCP Server Template

A production-ready TypeScript template for building MCP servers with dual transport support (stdio/HTTP), OAuth 2.1 foundations, SQLite caching, observability, and security features including PII sanitization and rate limiting.

Doris MCP Server

Backend service implementing the Model Control Panel protocol that connects to Apache Doris databases, allowing users to execute SQL queries, manage metadata, and potentially leverage LLMs for tasks like natural language to SQL conversion.

Time MCP Server

Enables LLMs to retrieve current time information for specific IANA timezones or the local system timezone. It provides accurate ISO 8601 timestamps and detects daylight saving time status for requested locations.

QuantumArchitect MCP

Enables AI agents to create, validate, evaluate, and score quantum circuits with support for multiple hardware platforms. Provides tools for generating quantum algorithms (Bell states, Grover's, VQE), simulating circuits, checking hardware compatibility, and assessing circuit quality metrics.

Trello MCP Server

Enables seamless integration between Claude and Trello via Nango authentication. Allows managing boards, lists, cards, comments, and attachments through natural language commands with complete Trello API coverage.

MCP Emulator Controller

Enables control of Android emulators (MumuEmulator or ADB-connected devices) through natural language, supporting app management, screen interactions (tap/swipe), screenshots, and device information retrieval.

Trello MCP Server

Enables AI assistants and automation tools to interact with Trello boards, lists, and cards through a standardized interface. Supports creating, moving, archiving cards, adding comments, managing labels, and performing batch operations across Trello workspaces.

JetsonMCP

Connects AI assistants to NVIDIA Jetson Nano systems for edge computing management, enabling natural language control of AI workloads, hardware optimization, and system administration tasks.

mcp-confluent

Una implementación de servidor MCP construida para interactuar con las API REST de Confluent Kafka y Confluent Cloud.

Claude-to-Gemini MCP Server

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

example-mcp-server-streamable-http

example-mcp-server-streamable-http

A Simple MCP Server and Client

Okay, here's a simple example of an MCP (Minecraft Communications Protocol) client and server in Python. This is a very basic illustration and doesn't cover all the complexities of a real MCP implementation. It focuses on establishing a connection, sending a simple message, and receiving a response. **Important Considerations:** * **Security:** This example is *not* secure. It transmits data in plain text. For any real-world application, you'd need to implement proper encryption (e.g., TLS/SSL). * **Error Handling:** The error handling is minimal. A robust implementation would need more comprehensive error checking and recovery. * **MCP Complexity:** Real MCP involves much more complex data structures, authentication, and message types. This is a simplified demonstration. * **Dependencies:** This example uses the standard `socket` library, which is built into Python. **Server (server.py):** ```python import socket HOST = '127.0.0.1' # Standard loopback interface address (localhost) PORT = 25565 # Port to listen on (non-privileged ports are > 1023) with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((HOST, PORT)) s.listen() print(f"Server listening on {HOST}:{PORT}") conn, addr = s.accept() with conn: print(f"Connected by {addr}") while True: data = conn.recv(1024) # Receive up to 1024 bytes if not data: break decoded_data = data.decode('utf-8') print(f"Received: {decoded_data}") # Simple response response = f"Server received: {decoded_data}".encode('utf-8') conn.sendall(response) ``` **Client (client.py):** ```python import socket HOST = '127.0.0.1' # The server's hostname or IP address PORT = 25565 # The port used by the server with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.connect((HOST, PORT)) message = "Hello, MCP Server!".encode('utf-8') s.sendall(message) data = s.recv(1024) print(f"Received: {data.decode('utf-8')}") ``` **How to Run:** 1. **Save:** Save the code as `server.py` and `client.py`. 2. **Run the Server:** Open a terminal or command prompt and run `python server.py`. The server will start listening for connections. 3. **Run the Client:** Open *another* terminal or command prompt and run `python client.py`. The client will connect to the server, send a message, and receive a response. **Explanation:** * **`socket.socket(socket.AF_INET, socket.SOCK_STREAM)`:** Creates a socket object. * `AF_INET`: Specifies the IPv4 address family. * `SOCK_STREAM`: Specifies a TCP socket (reliable, connection-oriented). * **`s.bind((HOST, PORT))` (Server):** Binds the socket to a specific address and port. * **`s.listen()` (Server):** Starts listening for incoming connections. * **`s.accept()` (Server):** Accepts a connection. This blocks until a client connects. It returns a new socket object (`conn`) representing the connection and the client's address (`addr`). * **`s.connect((HOST, PORT))` (Client):** Connects to the server at the specified address and port. * **`conn.recv(1024)` (Server & Client):** Receives data from the socket. The `1024` specifies the maximum number of bytes to receive at once. * **`conn.sendall(message)` (Server & Client):** Sends data to the socket. `sendall` ensures that all data is sent. * **`data.decode('utf-8')`:** Decodes the received bytes into a string using UTF-8 encoding. * **`message.encode('utf-8')`:** Encodes the string into bytes using UTF-8 encoding before sending. **Spanish Translation of Explanation:** * **`socket.socket(socket.AF_INET, socket.SOCK_STREAM)`:** Crea un objeto socket. * `AF_INET`: Especifica la familia de direcciones IPv4. * `SOCK_STREAM`: Especifica un socket TCP (confiable, orientado a la conexión). * **`s.bind((HOST, PORT))` (Servidor):** Vincula el socket a una dirección y puerto específicos. * **`s.listen()` (Servidor):** Comienza a escuchar las conexiones entrantes. * **`s.accept()` (Servidor):** Acepta una conexión. Esto se bloquea hasta que un cliente se conecta. Devuelve un nuevo objeto socket (`conn`) que representa la conexión y la dirección del cliente (`addr`). * **`s.connect((HOST, PORT))` (Cliente):** Se conecta al servidor en la dirección y el puerto especificados. * **`conn.recv(1024)` (Servidor y Cliente):** Recibe datos del socket. El `1024` especifica el número máximo de bytes para recibir a la vez. * **`conn.sendall(message)` (Servidor y Cliente):** Envía datos al socket. `sendall` asegura que todos los datos se envíen. * **`data.decode('utf-8')`:** Decodifica los bytes recibidos en una cadena utilizando la codificación UTF-8. * **`message.encode('utf-8')`:** Codifica la cadena en bytes utilizando la codificación UTF-8 antes de enviar. **Spanish Translation of Important Considerations:** * **Seguridad:** Este ejemplo *no* es seguro. Transmite datos en texto plano. Para cualquier aplicación del mundo real, necesitaría implementar un cifrado adecuado (por ejemplo, TLS/SSL). * **Manejo de errores:** El manejo de errores es mínimo. Una implementación robusta necesitaría una verificación y recuperación de errores más completa. * **Complejidad de MCP:** El MCP real implica estructuras de datos, autenticación y tipos de mensajes mucho más complejos. Esta es una demostración simplificada. * **Dependencias:** Este ejemplo utiliza la biblioteca estándar `socket`, que está integrada en Python. This provides a basic foundation. To build a more realistic MCP implementation, you would need to define specific message formats, handle different message types, implement authentication, and add robust error handling. Remember to prioritize security in any real-world application.

Pistachio MCP Server

A remote MCP server built with Node.js and TypeScript that enables tool calls and prompt templates via streamable HTTP transport. It includes example implementations for a calculator and localized greetings, featuring built-in CORS support for web-based clients.

Zerodha MCP Server

Enables trading operations on Zerodha platform through natural language, supporting account management, order placement/modification, portfolio holdings, positions, margins, and stock news retrieval.

Custom Search MCP Server

An MCP (Multi-Agent Conversation Protocol) Server that enables interaction with Google's Custom Search API, allowing agents to perform customized web searches through natural language requests.

File System MCP Server

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MCP Multi-Server System

A dual-server MCP system with PostgreSQL integration that provides financial tools (stock prices, portfolio calculation, financial news) on one server and utility tools (weather, time, data processing, text analysis) on another server.

Recash1 MCP Server

Enables access to the Recash1 API for searching and retrieving product information from a database, including filtering products and getting all products with their codes.

CodeRAG

A high-performance MCP server providing lightning-fast hybrid code search using TF-IDF and vector embeddings for AI assistants. It enables real-time codebase indexing and semantic retrieval with sub-50ms latency and offline support.

imagen-mcp

Enables intelligent multi-provider image generation through OpenAI and Google Gemini APIs with automatic provider selection, support for reference images, real-time data grounding, and conversational refinement.

Calculator MCP Server

A unified mathematical calculator that automatically detects expression types and performs basic arithmetic, statistical calculations, equation solving, and batch computations with 20+ built-in mathematical functions.

FDEP MCP Server

Provides static code analysis for enterprise-scale Haskell codebases with 40+ comprehensive tools for analyzing modules, functions, types, classes, imports, and architectural dependencies through real-time queries.

Z3 Theorem Prover with Functional Programming

Un servidor MCP para el demostrador de teoremas z3.