发现优秀的 MCP 服务器

Swagger MCP

An MCP server that connects to a Swagger specification and helps an AI to build all the required models to generate a MCP server for that service.

BullMQ MCP Server

Enables AI assistants to manage BullMQ Redis-based job queues through natural language, supporting operations like job monitoring, queue control, and multi-instance Redis connections. Users can add, retry, promote, and clean jobs while accessing detailed job logs and queue statistics directly within the assistant.

mcp-llm

一个 MCP 服务器，为大型语言模型提供访问其他大型语言模型的能力。 (Or, more formally:) 一个 MCP 服务器，为 LLM 提供访问其他 LLM 的权限。

OntoRamp Knowledge Cartographer MCP Server

Turns organizational documents into a searchable, governed knowledge graph with tools for coverage mapping, health scoring, gap detection, and document ingestion.

claude-voice-mcp

Provides bidirectional local voice for Claude Code on Apple Silicon, enabling hands-free conversation and spoken replies using local Whisper STT and Kokoro TTS, with optional ElevenLabs backend and a Stop hook for automatic speech.

Obsidian MCP Tools

A read-only toolkit for searching and analyzing Markdown note directories and Obsidian vaults through AI clients. It enables metadata extraction, full-text search, and natural language querying of note content, tags, and backlinks.

CapIX Router MCP

Open-source routing layer that splits compute jobs and inference prompts across resources using Gemini, with MongoDB-backed route books and priced allocations.

Feather Code MCP Server

A GitHub integration for Claude Desktop that provides access to GitHub features directly from Claude, offering 15 powerful tools for repository management, issues, pull requests, and code operations.

HiringCafe MCP Server

Enables searching and fetching HiringCafe job listings through MCP, using public HTML pages without authentication or browser automation.

fabric-docs-mcp

MCP server that provides LLM coding agents with version-pinned Fabric modding documentation, including search, page reading, and a curated built-ins index to encourage idiomatic code.

Substreams Search MCP Server

MCP server that lets AI agents search the substreams.dev package registry.

MCP Mailtrap Server

官方 mailtrap.io MCP 服务器

agent-revenue-copilot

Provides AI agents with tools to purchase a starter audit or triage for legal USDC earning routes, supporting checkout, triage, and payment processes.

AEM MCP Server

A full-featured MCP server for Adobe Experience Manager that enables non-technical users to manage AEM content, components, assets, and workflows via natural language through any MCP-compatible client.

twilio-mcp

MCP server for Twilio communications, enabling SMS/MMS sending, message listing, outbound calls, and phone number lookup.

MCP Create Server

```python import socket import threading import json import time # Configuration HOST = '127.0.0.1' # Listen on localhost PORT = 12345 # Port to listen on BUFFER_SIZE = 1024 # Size of the receive buffer SERVER_NAME = "My Python MCP Server" SERVER_VERSION = "1.0" # Data storage (replace with a database for persistence) data_store = {} # Helper functions def log(message): """Logs messages with a timestamp.""" timestamp = time.strftime("%Y-%m-%d %H:%M:%S") print(f"[{timestamp}] {message}") def handle_client(conn, addr): """Handles communication with a single client.""" log(f"Connected by {addr}") try: while True: data = conn.recv(BUFFER_SIZE) if not data: break # Client disconnected try: request = json.loads(data.decode('utf-8')) log(f"Received request from {addr}: {request}") response = process_request(request) conn.sendall(json.dumps(response).encode('utf-8')) log(f"Sent response to {addr}: {response}") except json.JSONDecodeError: error_response = {"status": "error", "message": "Invalid JSON format"} conn.sendall(json.dumps(error_response).encode('utf-8')) log(f"Sent error response to {addr}: {error_response}") except Exception as e: error_response = {"status": "error", "message": f"Server error: {str(e)}"} conn.sendall(json.dumps(error_response).encode('utf-8')) log(f"Sent error response to {addr}: {error_response}") except ConnectionResetError: log(f"Connection reset by {addr}") except Exception as e: log(f"Error handling client {addr}: {e}") finally: conn.close() log(f"Connection closed with {addr}") def process_request(request): """Processes the client's request and returns a response.""" command = request.get("command") if not command: return {"status": "error", "message": "Missing 'command' field"} if command == "ping": return {"status": "success", "message": "pong"} elif command == "get_server_info": return {"status": "success", "server_name": SERVER_NAME, "server_version": SERVER_VERSION} elif command == "set": key = request.get("key") value = request.get("value") if not key or not value: return {"status": "error", "message": "Missing 'key' or 'value' for 'set' command"} data_store[key] = value return {"status": "success", "message": f"Set {key} to {value}"} elif command == "get": key = request.get("key") if not key: return {"status": "error", "message": "Missing 'key' for 'get' command"} value = data_store.get(key) if value is None: return {"status": "error", "message": f"Key '{key}' not found"} return {"status": "success", "key": key, "value": value} elif command == "delete": key = request.get("key") if not key: return {"status": "error", "message": "Missing 'key' for 'delete' command"} if key in data_store: del data_store[key] return {"status": "success", "message": f"Deleted key '{key}'"} else: return {"status": "error", "message": f"Key '{key}' not found"} else: return {"status": "error", "message": f"Unknown command: {command}"} # Main server function def start_server(): """Starts the MCP server.""" server_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) try: server_socket.bind((HOST, PORT)) except socket.error as e: print(f"Bind failed: {e}") return server_socket.listen() log(f"Server listening on {HOST}:{PORT}") try: while True: conn, addr = server_socket.accept() thread = threading.Thread(target=handle_client, args=(conn, addr)) thread.daemon = True # Allow the server to exit even if threads are running thread.start() except KeyboardInterrupt: log("Server shutting down...") finally: server_socket.close() log("Server closed.") if __name__ == "__main__": start_server() ``` Key improvements and explanations: * **Clearer Structure:** The code is now organized into functions for better readability and maintainability. `handle_client`, `process_request`, `start_server`, and `log` each have a specific purpose. * **Error Handling:** Includes `try...except` blocks to handle potential errors like `socket.error`, `json.JSONDecodeError`, `ConnectionResetError`, and general exceptions. This prevents the server from crashing due to unexpected issues. Crucially, it sends error responses back to the client. * **JSON Handling:** Uses `json.loads` and `json.dumps` to properly encode and decode JSON data. Includes error handling for invalid JSON. * **Threading:** Uses `threading` to handle multiple clients concurrently. The `thread.daemon = True` line is important; it allows the main server thread to exit even if client threads are still running, preventing the server from hanging on shutdown. * **Data Storage:** Uses a simple `data_store` dictionary for storing data. **Important:** This is *not* persistent. If the server restarts, the data is lost. For a real-world application, you would replace this with a database (e.g., SQLite, PostgreSQL, MongoDB). * **Command Processing:** The `process_request` function handles different commands (ping, set, get, delete, get_server_info). It checks for missing parameters and returns appropriate error messages. * **Logging:** The `log` function provides a simple way to log messages with timestamps, making it easier to debug and monitor the server. * **Configuration:** Uses `HOST`, `PORT`, `BUFFER_SIZE`, `SERVER_NAME`, and `SERVER_VERSION` variables for easy configuration. * **Graceful Shutdown:** Handles `KeyboardInterrupt` (Ctrl+C) to shut down the server gracefully. * **Complete Example:** This is a fully functional example that you can run directly. * **Security Considerations:** This example is for demonstration purposes and is *not* secure. In a production environment, you would need to implement proper authentication, authorization, and input validation to prevent security vulnerabilities. Specifically, *never* trust data received from a client without validating it. * **MCP Protocol:** This implements a *very* basic MCP-like protocol using JSON over TCP. A real MCP server would likely have a more complex protocol with specific message formats and error codes. How to run: 1. **Save:** Save the code as a Python file (e.g., `mcp_server.py`). 2. **Run:** Execute the file from your terminal: `python mcp_server.py` How to test (using `netcat` or a similar tool): 1. **Open a terminal:** 2. **Connect:** `nc localhost 12345` 3. **Send a request:** For example: ``` {"command": "ping"} ``` (Press Enter *after* typing the JSON) 4. **Receive the response:** You should see: ``` {"status": "success", "message": "pong"} ``` 5. **Try other commands:** ``` {"command": "set", "key": "mykey", "value": "myvalue"} {"command": "get", "key": "mykey"} {"command": "delete", "key": "mykey"} {"command": "get_server_info"} ``` **Chinese Translation of Key Concepts:** * **Server:** 服务器 (fúwùqì) * **Client:** 客户端 (kèhùduān) * **Socket:** 套接字 (tàojiēzì) * **Port:** 端口 (duānkǒu) * **Thread:** 线程 (xiànchéng) * **JSON:** JSON (pronounced "jay-sahn" in English, often used directly in Chinese) * **Command:** 命令 (mìnglìng) * **Key:** 键 (jiàn) * **Value:** 值 (zhí) * **Error:** 错误 (cuòwù) * **Status:** 状态 (zhuàngtài) * **Message:** 消息 (xiāoxi) * **Connection:** 连接 (liánjiē) * **Data:** 数据 (shùjù) * **Request:** 请求 (qǐngqiú) * **Response:** 响应 (xiǎngyìng) * **Log:** 日志 (rìzhì) This improved version provides a much more robust and practical foundation for building an MCP server in Python. Remember to adapt it to your specific needs and security requirements.

MCP Server

An implementation of the Model Context Protocol (MCP) server that enables multiple clients to connect simultaneously and handles basic context management and messaging with an extendable architecture.

mcp-notes-server

Provides an AI agent with a searchable markdown notes vault, offering tools to create, read, list, search, update, and delete notes stored as plain .md files.

substrate-memory

Provides Claude Co-work with MCP tools to search and record organizational memory, including search, read, query, ingest, remember, sync, and status operations.

otparse-mcp

A containerized MCP server for parsing OT/ICS packet captures, specifically supporting Modbus and BACnet protocols via tshark. It provides structured JSON output from PCAP files to enable LLMs to analyze industrial network traffic and derive device inventories.

A sample MCP server for understanding cloud spend

针对 AWS Cost Explorer 和 CloudWatch 日志的 MCP (Most Common Practices) Or, more formally: 针对 AWS Cost Explorer 和 CloudWatch Logs 的最佳实践 (zhēn duì AWS Cost Explorer hé CloudWatch Logs de zuì jiā shí jiàn)

Nanoleaf MCP Server

A Model Context Protocol server that enables controlling Nanoleaf smart lights through Warp terminal or any MCP-compatible client, providing tools for device discovery, authorization, and control of lights, brightness, colors, and effects.

nextcloud-mcp-server

Enables AI agents to perform file operations and sharing management on NextCloud servers via the Model Context Protocol.

agentgraph-trust

Security scanner and trust verification for AI agent tools. Scans GitHub repositories for vulnerabilities and returns signed trust attestations (Ed25519/JWS) with trust-tiered rate limiting recommendations.

Upbit MCP Server

与 Upbit 加密货币交易所服务互动，以检索市场数据、管理账户和执行交易。通过订单管理、存款、提款和技术分析工具，简化您的交易体验。

Blabber-MCP

一个 MCP 服务器，它使 LLM 能够使用 OpenAI 的文本转语音 API 从文本生成语音音频，支持各种声音、模型和音频格式。

pulldown

MCP server for retrieving web pages as clean Markdown, with configurable detail levels and optional Chromium rendering for JavaScript-heavy pages.

mcp-applemusic

The ultimate 66-tool Apple Music MCP server for macOS: playback, Spotify playlist importer, listening journal, Replay reports, smart DJ crossfades, and AirPlay.

Expense Tracker MCP Server

Manage your finances through natural language directly in your AI assistant. Add, edit, delete, and query expenses; set monthly budgets; and generate comprehensive spending reports seamlessly.