Discover Awesome MCP Servers

SiteBay MCP Server

Enables management of WordPress sites hosted on SiteBay platform through natural language, including site creation, executing WP-CLI commands, file editing, and server operations.

Remote MCP Server (Authless)

A template for deploying an MCP server without authentication on Cloudflare Workers. Allows connection from Claude Desktop and AI Playground to use custom tools remotely.

MindBridge MCP Server

一个 AI 路由器，可以将应用程序连接到多个 LLM 提供商（OpenAI、Anthropic、Google、DeepSeek、Ollama 等），并具备智能模型编排能力，从而能够针对不同的推理任务在模型之间进行动态切换。

MCP-RLM

An implementation of the Recursive Language Models architecture that enables AI agents to process massive documents by programmatically decomposing them into sub-queries. It allows for cost-effective and accurate reasoning across millions of tokens by treating long-form data as an external environment for root and worker models.

Shopify MCP Server

通过 GraphQL API 实现与 Shopify 商店的交互，提供管理产品、客户、订单等工具。

IPA MCP Server

Enables management of FreeIPA resources including user groups, host groups, HBAC, and sudo rules via the FreeIPA JSON-RPC API. It provides comprehensive tools for automating access control and infrastructure provisioning in FreeIPA-managed environments.

Todoist MCP Server

A self-hosted MCP server that wraps the official Todoist AI package to provide over 35 tools for managing tasks and projects. It features a Dockerized setup with automatic TLS, enabling seamless integration with AI clients like Claude and Cursor.

simple-mcp-runner

Simple MCP Runner makes it effortless to safely expose system commands to language models via a lightweight MCP server—all configurable with a clean, minimal YAML file and zero boilerplate.

Code Search MCP

Enables LLMs to perform high-performance code search and analysis across multiple languages using symbol indexing, regex text search, and structural AST pattern matching. It also provides tools for technology stack detection and dependency analysis with persistent caching for optimized performance.

octo-mcp-server

A production-ready MCP server built with Node.js and Express that supports remote deployment via HTTP and SSE. It provides a modular framework for building and scaling tools while serving multiple clients concurrently.

Multi-Agent Tools Platform

A modular production-ready system that provides specialized agents for math, research, weather, and summarization tasks through a unified MCP toolbox with smart supervisor capabilities.

TradeX MCP Server

Enables AI agents to research, analyze, and trade Pokemon card perpetual futures on the TradeX platform. It supports market data retrieval, trading simulations, and secure transaction execution using local Solana keypairs.

Browserbase MCP Server

Enables AI to control cloud browsers and automate web interactions through Browserbase and Stagehand. Supports web navigation, form filling, data extraction, screenshots, and automated actions with natural language commands.

Chotu Robo Server

An MCP server that integrates Arduino-based robotics (ESP32 or Arduino Nano) with AI, allowing control of hardware components like LEDs, motors, servos, and sensors through AI assistants.

RemoteZip MCP Server

Enables accessing and extracting files from remote zip archives over HTTP, HTTPS, and FTP without downloading the entire archive. Supports listing files, extracting individual files, and getting file information using partial reading techniques.

Up Bank MCP Server

An MCP wrapper for Up Bank's API that allows Claude and other MCP-enabled clients to manage accounts, transactions, categories, tags, and webhooks from Up Bank.

Ultimate All-in-One MCP Server

A comprehensive collection of 103 tools providing capabilities for text processing, data analysis, web development, and business management in a single server. It is designed for rapid deployment to Vercel and integrates seamlessly with MCP clients like Claude and Cursor to automate diverse workflows.

Gmail MCP Server

Enables AI assistants to manage Gmail by reading unread emails with automatic classification, creating AI-generated draft replies, and saving drafts directly to Gmail through the Gmail API.

lint-mcp

Enables intelligent Go code quality checking with smart change detection through golangci-lint integration. Automatically detects branch development scope and focuses on current changes to avoid historical code issues.

Magento 2 Development MCP Server

Enables AI agents to interact with Magento 2 development environments through comprehensive tools for module management, database operations, cache control, configuration management, and system diagnostics. Supports complete development workflows from module creation to deployment and troubleshooting.

MCP Server Basic

A basic MCP server example that provides simple arithmetic tools (addition and subtraction) and personalized greeting resources. Serves as a foundation for learning MCP server implementation and development.

mcp-server-demo

✨ MCP 服务器演示

TanStack MCP Server

Wraps the TanStack CLI to provide programmatic access to documentation, library listings, and project scaffolding for the TanStack ecosystem. It enables AI assistants to search documentation and create new TanStack applications through the Model Context Protocol.

mcp-server-chart

mcp-server-chart

Whoop MCP Server

Integrates WHOOP biometric data into Claude and other MCP-compatible applications, providing access to sleep analysis, recovery metrics, strain tracking, and biological age data through natural language queries.

SharePoint MCP: The .NET MCP Server with Graph API & Semantic Kernel

Okay, I understand. You want to create an **MCP (Message Center Provider) server** to access **SharePoint Online**. However, there's a potential misunderstanding here. "MCP server" isn't a standard term in the context of SharePoint Online development. It sounds like you're aiming to build a custom application or service that interacts with SharePoint Online data, possibly to receive and process notifications or updates. Therefore, I'll provide you with a general outline and explanation of how to build a service that can access SharePoint Online data, including how to handle notifications and changes. This will involve using the Microsoft Graph API and/or the SharePoint REST API. Here's a breakdown of the steps and considerations, along with the Chinese translation of key terms: **1. Understanding the Goal (理解目标)** * **English:** You want to create a service that can access and potentially react to changes in SharePoint Online. This might involve: * Retrieving data (lists, libraries, documents, etc.) * Monitoring for changes (new files, updated items, etc.) * Performing actions based on those changes (e.g., sending notifications, triggering workflows). * **Chinese:** 你想创建一个服务，可以访问并可能对 SharePoint Online 中的更改做出反应。 这可能涉及： * 检索数据（列表、库、文档等） * 监视更改（新文件、更新的项目等） * 根据这些更改执行操作（例如，发送通知、触发工作流）。 **2. Choosing an API (选择 API)** * **Microsoft Graph API (Microsoft Graph API):** This is the recommended approach for most new development. It provides a unified endpoint to access data across Microsoft 365, including SharePoint Online. It's generally easier to use and more feature-rich than the SharePoint REST API. * **SharePoint REST API (SharePoint REST API):** This is a more direct way to interact with SharePoint Online. It's useful if you need very specific control over SharePoint features. **3. Authentication and Authorization (身份验证和授权)** * **English:** Your service needs to authenticate with Azure Active Directory (Azure AD) to access SharePoint Online. You'll need to register an application in Azure AD and grant it the necessary permissions. There are two main authentication flows: * **Delegated Permissions (委派权限):** The application acts on behalf of a user. The user needs to grant consent to the application. * **Application Permissions (应用程序权限):** The application acts on its own behalf, without a user. This requires administrator consent. This is generally preferred for background services. * **Chinese:** 您的服务需要使用 Azure Active Directory (Azure AD) 进行身份验证才能访问 SharePoint Online。 您需要在 Azure AD 中注册一个应用程序，并授予它必要的权限。 有两种主要的身份验证流程： * **委派权限:** 应用程序代表用户行事。 用户需要授予应用程序同意。 * **应用程序权限:** 应用程序代表自己行事，无需用户。 这需要管理员同意。 这通常是后台服务的首选。 **4. Development Steps (开发步骤)** Here's a general outline of the development process, using the Microsoft Graph API as an example: * **Step 1: Register an Application in Azure AD (在 Azure AD 中注册应用程序)** * Go to the Azure portal (portal.azure.com). * Navigate to "Azure Active Directory" -> "App registrations". * Click "New registration". * Give your application a name (e.g., "SharePointDataService"). * Choose the appropriate account type (usually "Single tenant"). * Set the redirect URI (if needed; for a background service, this might not be necessary). * Click "Register". * Note the "Application (client) ID" and "Directory (tenant) ID". You'll need these later. * **Step 2: Grant API Permissions (授予 API 权限)** * In your Azure AD app registration, go to "API permissions". * Click "Add a permission". * Select "Microsoft Graph". * Choose "Application permissions" (for a background service). * Search for and select the necessary permissions. Common permissions include: * `Sites.Read.All` (Read SharePoint sites) * `Sites.ReadWrite.All` (Read and write SharePoint sites) * `Sites.Manage.All` (Full control of SharePoint sites) * `Files.Read.All` (Read all files) * `Files.ReadWrite.All` (Read and write all files) * Click "Add permissions". * **Important:** After adding application permissions, you need to grant admin consent. Click "Grant admin consent for [Your Tenant Name]". * **Step 3: Obtain an Access Token (获取访问令牌)** * You'll need to use a library like MSAL (Microsoft Authentication Library) to obtain an access token. The code will vary depending on your programming language. Here's a Python example using `msal`: ```python import msal # Replace with your actual values CLIENT_ID = "YOUR_CLIENT_ID" CLIENT_SECRET = "YOUR_CLIENT_SECRET" TENANT_ID = "YOUR_TENANT_ID" AUTHORITY = f"https://login.microsoftonline.com/{TENANT_ID}" SCOPES = ["https://graph.microsoft.com/.default"] # Use .default for application permissions app = msal.ConfidentialClientApplication( CLIENT_ID, authority=AUTHORITY, client_credential=CLIENT_SECRET ) result = app.acquire_token_for_client(scopes=SCOPES) if "access_token" in result: access_token = result["access_token"] print("Access Token:", access_token) else: print(result.get("error_description", "No error information available")) ``` * **Chinese:** ```python import msal # 替换为您的实际值 CLIENT_ID = "YOUR_CLIENT_ID" CLIENT_SECRET = "YOUR_CLIENT_SECRET" TENANT_ID = "YOUR_TENANT_ID" AUTHORITY = f"https://login.microsoftonline.com/{TENANT_ID}" SCOPES = ["https://graph.microsoft.com/.default"] # 使用 .default 作为应用程序权限 app = msal.ConfidentialClientApplication( CLIENT_ID, authority=AUTHORITY, client_credential=CLIENT_SECRET ) result = app.acquire_token_for_client(scopes=SCOPES) if "access_token" in result: access_token = result["access_token"] print("访问令牌:", access_token) else: print(result.get("error_description", "没有可用的错误信息")) ``` * **Step 4: Call the Microsoft Graph API (调用 Microsoft Graph API)** * Use the access token to make requests to the Microsoft Graph API. For example, to get a list of SharePoint sites: ```python import requests GRAPH_API_ENDPOINT = "https://graph.microsoft.com/v1.0/sites" headers = { "Authorization": f"Bearer {access_token}" } response = requests.get(GRAPH_API_ENDPOINT, headers=headers) if response.status_code == 200: sites = response.json() print("SharePoint Sites:", sites) else: print("Error:", response.status_code, response.text) ``` * **Chinese:** ```python import requests GRAPH_API_ENDPOINT = "https://graph.microsoft.com/v1.0/sites" headers = { "Authorization": f"Bearer {access_token}" } response = requests.get(GRAPH_API_ENDPOINT, headers=headers) if response.status_code == 200: sites = response.json() print("SharePoint 站点:", sites) else: print("错误:", response.status_code, response.text) ``` * **Step 5: Handle Changes and Notifications (处理更改和通知)** * **Microsoft Graph Change Notifications (Microsoft Graph 更改通知):** This is the recommended way to receive notifications about changes in SharePoint Online. You can subscribe to changes on specific resources (e.g., a list, a library, a file). When a change occurs, Microsoft Graph will send a notification to your service. You'll need to set up a webhook endpoint to receive these notifications. * **SharePoint Webhooks (SharePoint Webhooks):** An older method, but still supported. Similar to Microsoft Graph Change Notifications, but specific to SharePoint. * **Polling (轮询):** The least efficient method. Your service periodically checks for changes. Avoid this if possible. **5. Key Considerations (关键考虑因素)** * **Error Handling (错误处理):** Implement robust error handling to deal with API errors, authentication failures, and other issues. * **Rate Limiting (速率限制):** Be aware of Microsoft Graph API and SharePoint REST API rate limits. Implement retry logic and caching to avoid exceeding these limits. * **Security (安全):** Protect your client ID and client secret. Store them securely (e.g., using Azure Key Vault). * **Scalability (可扩展性):** Design your service to be scalable to handle a large number of requests and notifications. * **Permissions (权限):** Only request the minimum permissions required for your service to function. * **Monitoring (监控):** Implement monitoring to track the health and performance of your service. **Example: Setting up a Microsoft Graph Change Notification (示例：设置 Microsoft Graph 更改通知)** This is a simplified example. You'll need to adapt it to your specific requirements. 1. **Create a Webhook Endpoint (创建 Webhook 端点):** This is an HTTP endpoint that will receive notifications from Microsoft Graph. You'll need to make this endpoint publicly accessible (e.g., using Azure Functions, Azure App Service, or a similar service). 2. **Create a Subscription (创建订阅):** Use the Microsoft Graph API to create a subscription to the resource you want to monitor. For example, to subscribe to changes in a SharePoint list: ```python import requests import json GRAPH_API_ENDPOINT = "https://graph.microsoft.com/v1.0/subscriptions" WEBHOOK_URL = "YOUR_WEBHOOK_URL" # Replace with your webhook URL RESOURCE = "sites/{site-id}/lists/{list-id}/items" # Replace with your site and list IDs subscription_data = { "changeType": "created,updated,deleted", "notificationUrl": WEBHOOK_URL, "resource": RESOURCE, "expirationDateTime": "2024-12-31T23:59:00.0000000Z", # Adjust expiration date "clientState": "secretClientValue" # Optional, for validation } headers = { "Authorization": f"Bearer {access_token}", "Content-Type": "application/json" } response = requests.post(GRAPH_API_ENDPOINT, headers=headers, data=json.dumps(subscription_data)) if response.status_code == 201: subscription = response.json() print("Subscription created:", subscription) else: print("Error creating subscription:", response.status_code, response.text) ``` * **Chinese:** ```python import requests import json GRAPH_API_ENDPOINT = "https://graph.microsoft.com/v1.0/subscriptions" WEBHOOK_URL = "YOUR_WEBHOOK_URL" # 替换为您的 webhook URL RESOURCE = "sites/{site-id}/lists/{list-id}/items" # 替换为您的站点和列表 ID subscription_data = { "changeType": "created,updated,deleted", "notificationUrl": WEBHOOK_URL, "resource": RESOURCE, "expirationDateTime": "2024-12-31T23:59:00.0000000Z", # 调整过期日期 "clientState": "secretClientValue" # 可选，用于验证 } headers = { "Authorization": f"Bearer {access_token}", "Content-Type": "application/json" } response = requests.post(GRAPH_API_ENDPOINT, headers=headers, data=json.dumps(subscription_data)) if response.status_code == 201: subscription = response.json() print("订阅已创建:", subscription) else: print("创建订阅时出错:", response.status_code, response.text) ``` 3. **Handle the Notification (处理通知):** When a change occurs, Microsoft Graph will send a POST request to your webhook endpoint. Your endpoint needs to: * **Validate the request:** Verify the `clientState` (if you used it). * **Process the notification:** Extract the information about the change and take appropriate action. **Important Notes:** * This is a high-level overview. You'll need to consult the Microsoft Graph API documentation and SharePoint REST API documentation for detailed information. * The code examples are in Python, but you can use any programming language that supports HTTP requests. * Remember to replace the placeholder values (e.g., `YOUR_CLIENT_ID`, `YOUR_CLIENT_SECRET`, `YOUR_TENANT_ID`, `YOUR_WEBHOOK_URL`, `site-id`, `list-id`) with your actual values. * Consider using a framework like Flask or Django (for Python) to build your webhook endpoint. This comprehensive guide should help you get started with building a service to access SharePoint Online data and handle notifications. Remember to adapt the code and steps to your specific requirements. Good luck!

SuperCollider MCP Server

Enables execution of SuperCollider synth code through the Model Context Protocol using supercolliderjs, allowing AI assistants to generate and run audio synthesis programs.

mcp-nativewind

将 Tailwind 组件转换为 NativeWind 4。

Chess MCP Server

Enables Large Language Models to play chess agentically with real-time HTML board visualization and a hybrid AI engine featuring ten difficulty levels. It supports interactive games between users and agents, including a web dashboard to monitor active matches.

Azure Pricing MCP Server

Enables querying Azure retail pricing information, comparing costs across regions and SKUs, estimating usage-based expenses, and discovering Azure services with savings plan information through the Azure Retail Prices API.