Discover Awesome MCP Servers

Google Analytics MCP Server by CData

Google Analytics MCP Server by CData

MCP-IQWiki

A Model Context Protocol server that allows AI assistants and applications to access IQ.wiki data, enabling retrieval of specific wikis, user-created wikis, user-edited wikis, and detailed wiki activities.

MCP Router

A service discovery and proxy for MCP servers that enables registration, discovery, and execution of tools on remote MCP servers. Uses vector-based similarity search through Alibaba Cloud services to intelligently route requests to appropriate MCP services.

System Information MCP Server

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

JSON Compare MCP Server

Enables deep, order-independent comparison of JSON files to detect differences including missing keys, value mismatches, and type differences. Provides detailed reports with path tracking for precise identification of variations between JSON structures.

Graphistry MCP

GPU-accelerated graph visualization and analytics server for Large Language Models that integrates with Model Control Protocol (MCP), enabling AI assistants to visualize and analyze complex network data.

doc-tools-mcp

在 Node.js 中实现 Word 文档的读取和写入 MCP (Message Communication Protocol) 协议，需要分解成几个部分，并使用合适的库来处理 Word 文档和网络通信。 由于 MCP 通常指的是消息通信协议，与 Word 文档本身没有直接关系，因此我将假设你需要： 1. **读取和写入 Word 文档 (docx 格式)** 2. **使用 MCP 协议发送和接收 Word 文档的内容或相关信息** 以下是一个概念性的实现方案，包含代码示例和解释。 **1. 读取和写入 Word 文档 (docx 格式)** 可以使用 `docx` 库来处理 Word 文档。 ```bash npm install docx ``` ```javascript const { Document, Packer, Paragraph, TextRun } = require("docx"); const fs = require("fs"); // 创建一个新的 Word 文档 async function createWordDocument(data) { const doc = new Document({ sections: [{ children: [ new Paragraph({ children: [ new TextRun(data), ], }), ], }], }); // 将文档保存到文件 const buffer = await Packer.toBuffer(doc); fs.writeFileSync("my-document.docx", buffer); console.log("Word document created successfully!"); } // 读取 Word 文档 (需要额外的库，例如 mammoth.js) async function readWordDocument(filePath) { const mammoth = require("mammoth"); // 需要安装: npm install mammoth try { const result = await mammoth.extractRawText({ path: filePath }); const text = result.value; console.log("Word document content:", text); return text; } catch (error) { console.error("Error reading Word document:", error); return null; } } // 示例用法 async function main() { await createWordDocument("Hello, this is a test document created with Node.js!"); const content = await readWordDocument("my-document.docx"); if (content) { console.log("Successfully read the document."); } } main(); ``` **解释:** * **`docx` 库:** 用于创建和修改 Word 文档。 `Document`, `Paragraph`, `TextRun` 是 `docx` 库提供的类，用于构建文档结构。 * **`mammoth` 库:** 用于读取 Word 文档的内容。 `mammoth.extractRawText` 提取文档中的文本。 * **`fs` 模块:** Node.js 的文件系统模块，用于读写文件。 * **`createWordDocument` 函数:** 创建一个包含指定文本的 Word 文档，并将其保存到 `my-document.docx` 文件中。 * **`readWordDocument` 函数:** 读取指定路径的 Word 文档，并返回其文本内容。 **2. 使用 MCP 协议发送和接收 Word 文档的内容或相关信息** 这里需要定义 MCP 协议的具体格式。 假设 MCP 协议包含以下字段： * `type`: 消息类型 (例如 "document_content", "document_metadata") * `data`: 消息数据 (例如 Word 文档的内容，文档的元数据) 可以使用 Node.js 的 `net` 模块创建 TCP 服务器和客户端，并使用自定义的 MCP 协议进行通信。 ```javascript const net = require("net"); // MCP 协议编码函数 function encodeMCP(type, data) { const message = JSON.stringify({ type, data }); const length = Buffer.byteLength(message, 'utf8'); const lengthBuffer = Buffer.alloc(4); // 4 字节表示消息长度 lengthBuffer.writeInt32BE(length, 0); return Buffer.concat([lengthBuffer, Buffer.from(message, 'utf8')]); } // MCP 协议解码函数 function decodeMCP(buffer) { const length = buffer.readInt32BE(0); const message = buffer.slice(4, 4 + length).toString('utf8'); return JSON.parse(message); } // 服务器端 function startServer(port) { const server = net.createServer((socket) => { console.log("Client connected."); let receivedData = Buffer.alloc(0); socket.on("data", (data) => { receivedData = Buffer.concat([receivedData, data]); while (receivedData.length >= 4) { const length = receivedData.readInt32BE(0); if (receivedData.length >= 4 + length) { const messageBuffer = receivedData.slice(0, 4 + length); const message = decodeMCP(messageBuffer); console.log("Received message:", message); // 处理消息 if (message.type === "document_content") { console.log("Received document content:", message.data); } receivedData = receivedData.slice(4 + length); // 移除已处理的消息 } else { break; // 等待更多数据 } } }); socket.on("end", () => { console.log("Client disconnected."); }); socket.on("error", (err) => { console.error("Socket error:", err); }); }); server.listen(port, () => { console.log(`Server listening on port ${port}`); }); } // 客户端 function connectToServer(port, message) { const client = net.createConnection({ port: port }, () => { console.log("Connected to server."); const encodedMessage = encodeMCP(message.type, message.data); client.write(encodedMessage); }); client.on("data", (data) => { console.log("Received data from server:", data.toString()); client.end(); }); client.on("end", () => { console.log("Disconnected from server."); }); client.on("error", (err) => { console.error("Client error:", err); }); } // 示例用法 async function main() { const port = 8080; // 启动服务器 startServer(port); // 等待服务器启动 await new Promise(resolve => setTimeout(resolve, 1000)); // 读取 Word 文档内容 const documentContent = await readWordDocument("my-document.docx"); if (documentContent) { // 创建 MCP 消息 const message = { type: "document_content", data: documentContent, }; // 连接到服务器并发送消息 connectToServer(port, message); } } main(); ``` **解释:** * **`net` 模块:** Node.js 的网络模块，用于创建 TCP 服务器和客户端。 * **`encodeMCP` 函数:** 将消息编码为 MCP 协议格式。 它将消息类型和数据转换为 JSON 字符串，然后计算字符串的长度，并将长度作为 4 字节的大端整数添加到消息的前面。 * **`decodeMCP` 函数:** 将 MCP 协议格式的消息解码为 JavaScript 对象。 它首先读取消息长度，然后读取消息内容，并将其解析为 JSON 对象。 * **`startServer` 函数:** 启动一个 TCP 服务器，监听指定端口。 当客户端连接时，它会接收数据，解码 MCP 消息，并处理消息。 * **`connectToServer` 函数:** 连接到指定端口的 TCP 服务器，并发送 MCP 消息。 * **示例用法:** 首先启动服务器，然后读取 Word 文档的内容，创建一个包含文档内容的 MCP 消息，并将其发送到服务器。 **关键点:** * **MCP 协议定义:** 你需要根据实际需求定义 MCP 协议的格式。 上面的示例使用 JSON 格式，并添加了消息长度字段。 * **错误处理:** 在实际应用中，需要添加更完善的错误处理机制，例如处理网络连接错误，数据解析错误等。 * **数据分块:** 如果 Word 文档非常大，可能需要将文档内容分成多个块进行传输。 * **安全性:** 如果需要传输敏感数据，需要考虑使用加密技术，例如 TLS/SSL。 * **库的选择:** `docx` 和 `mammoth` 只是处理 Word 文档的其中两种库。 还有其他的库，例如 `officegen`，可以用于创建更复杂的 Word 文档。 选择合适的库取决于你的具体需求。 **总结:** 这个方案提供了一个基本的框架，用于在 Node.js 中实现 Word 文档的读取和写入，并使用 MCP 协议进行通信。 你需要根据实际需求调整代码，并添加必要的错误处理和安全性措施。 记住安装所需的 npm 包：`npm install docx mammoth`。 如果需要更复杂的 Word 文档处理功能，可以考虑使用其他的 Word 文档处理库。

XHS MCP

Enables interaction with Xiaohongshu (Little Red Book) platform through automated browser operations. Supports authentication, content publishing, search, discovery, and commenting using Puppeteer-based automation.

Useful-mcps

以下是一些实用的小型 MCP 服务器，包括： * docx\_replace：替换 Word 文档中的标签 * yt-dlp：基于章节提取章节和字幕 * mermaid：使用 mermaidchart.com API 生成和渲染图像

Remote MCP Server (Authless)

A deployable Cloudflare Workers service that implements Model Context Protocol without authentication, allowing AI models to access custom tools via clients like Claude Desktop or Cloudflare AI Playground.

QGISMCP

一个模型上下文协议服务器，将 Claude AI 连接到 QGIS，从而能够通过自然语言提示直接与 GIS 软件交互，以实现项目创建、图层操作、代码执行和处理算法。

MCP RSS News Agent

A FastMCP-based server that provides tools for discovering RSS feeds, fetching and processing news content, searching articles by keyword, and generating summaries across multiple news sources and categories.

video-transcribe-mcp

一个集成了 Optivus 的 MCP 服务器实现，为 LLM 提供视频转录功能（例如 YouTube、Facebook、Tiktok 等）。

Python MCP Server

**python-mcp-server** 项目是一个基于 Flask 的 Web 服务器，旨在与 Minecraft 交互，很可能是一个用于管理 Minecraft 服务器、插件或玩家数据的更大型系统的一部分。

Git MCP

Enables comprehensive Git and GitHub operations through 30 DevOps tools including repository management, file operations, workflows, and advanced Git features. Provides complete Git functionality without external dependencies for seamless integration with Gitea and GitHub platforms.

Google Drive MCP Server

好的，我们来一起创建一个 Google Drive MCP 服务器，首先从 Google Sheets 开始。 (Hǎo de, wǒmen lái yīqǐ chuàngjiàn yī ge Google Drive MCP fúwùqì, shǒuxiān cóng Google Sheets kāishǐ.) Okay, let's create a Google Drive MCP server together, starting with Google Sheets.

lafe-blog MCP Server

Enables creating and managing text notes with a simple note-taking system. Provides tools to create notes, access them via URIs, and generate summaries of all stored notes.

Signal MCP

An MCP integration for signal-cli that allows AI agents to send and receive Signal messages, supporting direct messages, group messages, and async message handling.

MCP Fullstack

A comprehensive operations platform providing browser automation, web search/crawling, database operations, deployment tools, secrets management, and analytics capabilities for full-stack software engineering workflows. Features AI-driven automation, real-time monitoring dashboard, and cross-platform service management.

MCP PDF

Enables creative PDF generation with full design control including colors, shapes, emoji, and Unicode support. Supports everything from simple documents to artistic masterpieces using PDFKit's powerful API.

Netlify Express MCP Server

A basic serverless MCP implementation using Netlify Functions and Express. Demonstrates how to deploy and run Model Context Protocol servers in a serverless environment with proper routing configuration.

Comax Payment Link MCP

Allows integration with Comax ERP/payment systems to create payment links, manage orders, and retrieve customer information using the MCP protocol.

MCP Storyblok Server

A comprehensive server enabling natural language interaction with Storyblok CMS for managing stories, assets, components, releases, and other content through a modular architecture.

OpenAPI MCP Server

一个服务器，它使大型语言模型能够通过模型上下文协议发现和交互由 OpenAPI 规范定义的 REST API。

MCP Server

A local middleware Node.js application for Windows that enables seamless communication between LLM-based tools like Copilot Agents, providing access to local guide files and custom prompts through built-in tools.

Brevo MCP Server

A comprehensive MCP server providing Claude with full access to Brevo's marketing automation platform through the official SDK, featuring tools for email operations, contact management, campaigns, SMS, conversations, webhooks, e-commerce, and account management.

brain-trust

Enables AI agents to ask questions and review planning documents by connecting to OpenAI's GPT-4. Provides context-aware question answering and multi-level plan analysis with structured feedback including strengths, weaknesses, and suggestions.

Fusion MCP

A Model Context Protocol server that connects LLMs with Autodesk Fusion, enabling CAD operations through natural language dialogue.

Airtable MCP Server

Enables complete interaction with Airtable databases through 16 CRUD operations including batch processing, schema management, and record manipulation. Designed for AI applications and n8n workflows with HTTP streaming support.