Discover Awesome MCP Servers

MCP Server Framework

A general-purpose MCP server that provides utility tools for echo, date/time, and file operations within Claude Code and Claude Desktop. It functions as an extensible framework designed to help developers easily build and register custom Python-based tools.

Example MCP Server

A simple demonstration MCP server that provides a basic 'say_hello' tool for greeting users by name, serving as a template for building MCP servers with TypeScript.

MCP Framework

Một framework TypeScript để xây dựng các máy chủ Model Context Protocol (MCP) với khả năng tự động khám phá và tải các công cụ, tài nguyên và lời nhắc.

Filesystem MCP Server

Enables comprehensive filesystem operations including reading/writing files, directory management, file searching, editing with diff preview, compression, hashing, and merging with dynamic directory access control.

Cosmos DB MCP Server by CData

Cosmos DB MCP Server by CData

Model Context Provider (MCP) Server

Tạo điều kiện tương tác nâng cao với các mô hình ngôn ngữ lớn (LLM) bằng cách cung cấp khả năng quản lý ngữ cảnh thông minh, tích hợp công cụ và điều phối mô hình AI đa nhà cung cấp để có quy trình làm việc dựa trên AI hiệu quả.

NewRelic MCP Server

A comprehensive MCP server providing over 26 tools for querying, monitoring, and analyzing NewRelic data through NRQL queries and entity management. It enables interaction with NewRelic's NerdGraph API for managing alerts, logs, and incidents directly within Claude Code sessions.

Cursor10x MCP

The Cursor10x Memory System creates a persistent memory layer for AI assistants (specifically Claude), enabling them to retain and recall short-term, long-term and episodic memory on autonomously.

Wealthfolio MCP Server

Enables AI-powered portfolio analysis for Wealthfolio, allowing Claude to query and analyze investment holdings, asset allocation, real estate properties, and execute transactions through natural language.

Customer Registration MCP Server

Enables creating and managing customer records via an external API with Bearer token authentication, supporting required fields (name, email, phone) and extensive optional data including addresses, UTM parameters, and tags.

TestRail MCP Server

Enables comprehensive TestRail test management integration with support for projects, test cases, runs, results, advanced reporting, analytics, and AutoSpectra test automation framework synchronization.

aiohttp-mcp

Here are some tools and libraries that can help you build Model Context Protocol (MCP) servers on top of aiohttp in Python: **Core Libraries:** * **aiohttp:** (As you mentioned) This is the fundamental asynchronous HTTP server and client library for Python. You'll use it to handle incoming requests, route them to the appropriate handlers, and send responses. It provides the basic building blocks for your MCP server. * **asyncio:** aiohttp is built on top of `asyncio`, Python's built-in asynchronous I/O framework. You'll need to understand `asyncio` concepts like event loops, coroutines (`async def`), and tasks to effectively use aiohttp. **Libraries for MCP Specifics (Depending on your MCP implementation):** * **Serialization/Deserialization Libraries (for handling MCP messages):** * **protobuf (Protocol Buffers):** If your MCP uses Protocol Buffers for message encoding, you'll need the `protobuf` library and the `grpcio-tools` package (for generating Python code from your `.proto` definitions). This is a very common choice for MCP due to its efficiency and schema definition capabilities. You'll likely use `asyncio` compatible protobuf libraries. Look for examples of using protobuf with `aiohttp`. * **msgpack:** A binary serialization format that's often faster than JSON. The `msgpack` library provides Python bindings. There are `asyncio` compatible versions or wrappers you might need to use. * **JSON:** If your MCP uses JSON, Python's built-in `json` module is sufficient. However, for very high performance, consider `orjson` which is a faster JSON library. * **Other Binary Serialization Formats:** Depending on the specific MCP, you might need libraries for other binary formats like Apache Avro or Thrift. * **Schema Validation (if your MCP requires it):** * **jsonschema:** For validating JSON payloads against a JSON Schema. Useful if your MCP uses JSON and has a defined schema. * **Cerberus:** A lightweight and extensible data validation library. Can be used for validating dictionaries or other data structures. * **gRPC (if your MCP is based on gRPC):** * **grpcio:** The core gRPC library for Python. While gRPC is often used with HTTP/2, you *might* be able to adapt it to work with aiohttp, but this is generally not the recommended approach. gRPC has its own server implementation. If you're using gRPC, you'd typically use the gRPC server directly, not aiohttp. However, you *could* potentially use aiohttp for other parts of your application and gRPC for the MCP endpoint. **Helper Libraries and Patterns:** * **aiohttp-middlewares:** aiohttp supports middlewares, which are functions that can intercept and process requests and responses. You can use middlewares for things like: * Authentication/Authorization * Logging * Request validation * Error handling * **Dependency Injection (e.g., `dependency_injector`):** If your MCP server has complex dependencies (e.g., database connections, model loaders), consider using a dependency injection framework to manage them. This makes your code more testable and maintainable. * **Configuration Management (e.g., `configparser`, `python-decouple`):** Use a library to manage your server's configuration (e.g., port number, database connection strings, model paths). * **Logging (e.g., `logging` module):** Implement proper logging to track requests, errors, and other important events. **Example Structure (Conceptual):** ```python import asyncio import aiohttp from aiohttp import web import logging # Example: Using protobuf # import my_mcp_pb2 # Generated protobuf code # import my_mcp_pb2_grpc # Configure logging logging.basicConfig(level=logging.INFO) async def handle_mcp_request(request): """Handles an incoming MCP request.""" try: # 1. Read the request body (e.g., as bytes) request_body = await request.read() # 2. Deserialize the request body (e.g., using protobuf) # message = my_mcp_pb2.MyRequestMessage() # message.ParseFromString(request_body) # 3. Process the request (e.g., call a model) # result = await process_model(message) # 4. Serialize the response (e.g., using protobuf) # response_message = my_mcp_pb2.MyResponseMessage() # response_message.result = result # response_body = response_message.SerializeToString() # Example using JSON data = await request.json() result = await process_model(data) response_body = web.json_response({"result": result}) # 5. Return the response return response_body except Exception as e: logging.exception("Error handling MCP request") return web.json_response({"error": str(e)}, status=500) # Or appropriate error code async def process_model(data): """Simulates processing a model based on the request.""" # Replace this with your actual model processing logic await asyncio.sleep(0.1) # Simulate some work return f"Model processed data: {data}" async def create_app(): """Creates the aiohttp application.""" app = web.Application() app.add_routes([web.post('/mcp', handle_mcp_request)]) # MCP endpoint return app async def main(): """Runs the aiohttp server.""" app = await create_app() runner = web.AppRunner(app) await runner.setup() site = web.TCPSite(runner, 'localhost', 8080) await site.start() logging.info("Server started on http://localhost:8080") try: await asyncio.Future() # Run forever finally: await runner.cleanup() if __name__ == '__main__': asyncio.run(main()) ``` **Key Considerations:** * **Asynchronous Operations:** Ensure that all I/O-bound operations (e.g., reading from the network, writing to a database, calling a model) are performed asynchronously using `async` and `await`. This is crucial for the performance of your aiohttp server. * **Error Handling:** Implement robust error handling to catch exceptions and return appropriate error responses to the client. Use logging to track errors. * **Concurrency:** aiohttp handles concurrency using `asyncio`. You don't typically need to manage threads directly. However, be aware of potential bottlenecks in your code (e.g., CPU-bound operations) and consider using a process pool executor (`asyncio.get_running_loop().run_in_executor`) to offload those operations to separate processes. * **Security:** If your MCP server handles sensitive data, implement appropriate security measures, such as authentication, authorization, and encryption (HTTPS). * **Performance:** Profile your server to identify performance bottlenecks and optimize accordingly. Consider using caching to reduce the load on your models. * **Testing:** Write thorough unit tests and integration tests to ensure that your MCP server is working correctly. Use `aiohttp.test_utils` for testing aiohttp applications. Remember to adapt these suggestions to the specific requirements of your Model Context Protocol. Good luck!

Minted MCP Server

Enables interaction with Minted.com to retrieve address book contacts, order history, and delivery information for recent card orders.

Webots MCP Server

Enables real-time monitoring and control of any Webots robot simulation, providing access to robot state, sensors, camera feeds, and simulation controls (pause, resume, reset) through natural language.

MCP Workflow Tracker

Provides observability for multi-agent workflows by tracking hierarchical task structure, architectural decisions, reasoning, encountered problems, code modifications with Git diffs, and temporal metrics.

LibreOffice MCP Server

Enables AI assistants to create, read, convert, and manipulate LibreOffice documents programmatically, supporting 50+ file formats including Writer, Calc, Impress documents with real-time editing, batch operations, and document analysis capabilities.

2slides MCP Server

Enables users to generate presentation slides using 2slides.com's API through Claude Desktop. Supports searching for slide themes, generating slides from text input, and monitoring job status for slide creation.

armavita-quo-mcp

Local-first MCP server for Quo/OpenPhone automation across messaging, calls, contacts, users, phone numbers, and webhooks via a clean stdio tool surface.

Discord MCP Server

A secure server that enables interaction with Discord channels through JWT-authenticated API calls, allowing users to send messages, fetch channel data, search content, and perform moderation actions.

EnrichB2B MCP Server

Một máy chủ triển khai Giao thức Ngữ cảnh Mô hình (Model Context Protocol) cho phép người dùng truy xuất thông tin hồ sơ LinkedIn và dữ liệu hoạt động thông qua API EnrichB2B, đồng thời tạo văn bản bằng các mô hình OpenAI GPT-4 hoặc Anthropic Claude.

product-hunt-mcp

product-hunt-mcp

opendart-fss-mcp

An MCP server that provides access to Korea's DART corporate disclosure system, offering 84 tools for retrieving financial statements, periodic reports, and shareholding information. It enables users to programmatically query and analyze official Korean corporate data via the OpenDART API.

Health MCP Server

Aggregates and analyzes fitness data from multiple sources like Whoop and Strava through a modular adapter architecture. It enables users to monitor health metrics, track activities, and gain insights into sleep, recovery, and training performance.

Hava Durumu MCP Server

Provides weather data using Open-Meteo API with support for current weather, 24-hour forecasts, and 7-day forecasts for Turkish cities and coordinate-based queries.

medRxiv MCP Server

Gương của

Spotify MCP Server

Máy chủ MCP để giao tiếp với Splunk

hive

Context infrastructure for AI-assisted development — on-demand Obsidian vault access via MCP

Hashkey MCP Server

A Model Context Protocol server that provides onchain tools for AI applications to interact with the Hashkey Network, enabling cryptocurrency transfers, smart contract deployment, and blockchain interactions.

FineData MCP Server

Enables AI agents to scrape any website by providing tools for JavaScript rendering, antibot bypass, and automatic captcha solving. It supports synchronous, asynchronous, and batch scraping operations with built-in proxy rotation.