Discover Awesome MCP Servers

Track-It Process Monitor

Enables Claude to monitor and inspect running processes through a lightweight wrapper that captures stdout/stderr logs and stores process metadata in SQLite. Users can track any command execution and query process status, logs, and history through natural language.

raindrop-mcp

Raindrop.io (书签服务) 的 MCP 服务器

MCP Think

A Model Context Protocol server that provides AI assistants like Claude with a dedicated space for structured thinking during complex problem-solving tasks.

Model Context Protocol (MCP) Server

A Python implementation of the MCP server that enables AI models to connect with external tools and data sources through a standardized protocol, supporting tool invocation and resource access via JSON-RPC.

Elasticsearch MCP Server

Enables Claude Desktop to connect directly to Elasticsearch clusters for intelligent log analysis through natural language queries. Users can ask questions about their logs in plain English and get actionable insights without writing complex Elasticsearch queries.

Enterprise Template Generator

Enables generation of enterprise-grade software templates with built-in GDPR/Swedish compliance validation, workflow automation for platform migrations, and comprehensive template management through domain-driven design principles.

缔零法则Lawgenesis

缔零法则MCP是基于LLM和RAG技术搭建的实现完全替代人力的全自动化风险识别的内容安全审查平台，致力于通过代理AI技术减少人力成本，高效高精度为用户提供分钟级接入的内容风控解决方案，破解安全威胁，提供从风险感知到主动拦截策略执行的全链路闭环与一体化解决方案。This MCP tool is an AI-powered content security review platform built on LLM and RAG technologies, designed to achieve fully automated risk identification that completel

Parallels RAS MCP Server (Python)

Here are a few possible translations, depending on the nuance you want to convey: **Option 1 (Most Direct):** * **Simplified Chinese:** 使用 FastAPI 的 Parallels RAS 的 MCP 服务器 * **Traditional Chinese:** 使用 FastAPI 的 Parallels RAS 的 MCP 伺服器 This is a straightforward translation. It's clear and accurate. **Option 2 (Slightly More Natural, Emphasizing "Built with"):** * **Simplified Chinese:** 基于 FastAPI 的 Parallels RAS MCP 服务器 * **Traditional Chinese:** 基於 FastAPI 的 Parallels RAS MCP 伺服器 This option uses "基于" (jī yú) which translates to "based on" or "built upon." It implies that the MCP server is constructed using FastAPI. **Option 3 (More Descriptive, Emphasizing "For"):** * **Simplified Chinese:** 用于 Parallels RAS 的基于 FastAPI 的 MCP 服务器 * **Traditional Chinese:** 用於 Parallels RAS 的基於 FastAPI 的 MCP 伺服器 This option uses "用于" (yòng yú) which translates to "for" or "intended for." It emphasizes that the MCP server is designed to be used with Parallels RAS. **Which one should you use?** * If you just need a simple, direct translation, **Option 1** is fine. * If you want to emphasize that the server is *built using* FastAPI, **Option 2** is better. * If you want to emphasize that the server is *designed for* Parallels RAS, **Option 3** is best. In most cases, **Option 1 or 2** will be the most appropriate. Choose the one that best fits the context.

Vercel Functions MCP Server Template

A template for deploying MCP servers on Vercel with serverless functions. Includes example tools for rolling dice and fetching weather data to demonstrate basic tool implementation and API integration patterns.

Claude Code DingTalk MCP Server

Integrates Claude Code with DingTalk (钉钉) robot notifications, allowing users to send task completion alerts and various message formats to DingTalk groups from Claude Code.

Devici MCP Server

Provides LLM tools to interact with the Devici API, enabling management of threat modeling resources including users, collections, threat models, components, threats, mitigations, and teams.

Bear MCP Server

Enables AI assistants to search, read, and browse Bear notes directly from your local Bear database. Supports searching by title, content, or tags, opening specific notes, and exploring tag-based organization.

46elks MCP Server

Enables AI assistants and MCP-compatible clients to send and manage SMS messages through the 46elks API, leveraging Swedish telecommunications infrastructure.

MCP JSON Database Server

A JSON-based database MCP server with JWT authentication that enables user management, project tracking, department analysis, meeting management, and equipment tracking. Integrates with Claude Desktop to provide secure CRUD operations and analytics through natural language commands.

mcp-test

test

Reality Calendar MCP Server

Enables interaction with tool data stored in Google Drive Excel files through cached SQLite database. Provides access to tool information and descriptions with automatic background synchronization and OpenWebUI compatibility via OpenAI proxy.

Storyblok MCP Server

Enables comprehensive management of Storyblok CMS through natural language interactions. Supports story creation and publishing, asset management, component schema updates, release workflows, and content discovery across all major Storyblok APIs.

LicenseSpring MCP Server

An MCP server implementation that integrates with LicenseSpring APIs, providing comprehensive license management and customer operations capabilities.

Test Generator MCP Server

Enables automatic generation of test scenarios from user stories uploaded to Claude desktop. Leverages MCP integration to streamline the test case creation process for development workflows.

MCP Weather Server

Enables AI agents to access real-time and historical weather data through multiple weather APIs including OpenMeteo, Tomorrow.io, and OpenWeatherMap. Provides comprehensive meteorological information including current conditions, forecasts, historical data, and weather alerts.

tasksync-mcp

MCP server to give new instructions to agent while its working. It uses the get_feedback tool to collect your input from the feedback.md file in the workspace, which is sent back to the agent when you save.

x64dbg MCP server

x64dbg 调试器的 MCP 服务器

Protein MCP Server

Enables searching, retrieving, and downloading protein structure data from the RCSB Protein Data Bank. Supports intelligent protein structure search, comprehensive data retrieval, and multiple file format downloads for bioinformatics research.

MyWeight MCP Server

A server that connects to the Health Planet API to fetch and provide weight measurement data through any MCP-compatible client, allowing for retrieval and analysis of personal weight records.

Uber External Ads API MCP Server

Enables users to manage Uber advertising campaigns through natural language by providing access to Uber's External Ads API. Supports campaign creation, retrieval, updating, and deletion with comprehensive filtering and configuration options.

Finizi B4B MCP Server

Enables AI assistants to interact with the Finizi B4B platform through 15 comprehensive tools for managing business entities, invoices, vendors, and products. Features secure JWT authentication, automatic retries, and comprehensive business data operations through natural language commands.

XFetch Mcp

更强大的 Fetch。 允许从任何网页检索内容，包括那些受 Cloudflare 和其他安全系统保护的网页。

Bocha Search MCP

一个以人工智能为中心的搜索引擎，使人工智能应用程序能够访问来自数十亿网页和生态系统内容源的高质量知识，涵盖各种领域，包括天气、新闻、百科全书、医疗信息、火车票和图像。

Accounting MCP Server

Enables personal financial management through AI assistants by providing tools to add transactions, check balances, list transaction history, and generate monthly summaries. Supports natural language interaction for tracking income and expenses with categorization.

Build

Okay, I can help you understand how to use the TypeScript SDK to create different MCP (Mesh Configuration Protocol) servers. However, I need a little more context to give you the *most* helpful answer. Specifically, tell me: 1. **Which MCP SDK are you using?** There are several possibilities, including: * **Istio's MCP SDK (likely part of the `envoyproxy/go-control-plane` project, but you'd be using the TypeScript bindings).** This is the most common use case if you're working with Istio or Envoy. * **A custom MCP implementation.** If you're building your own MCP server from scratch, you'll need to define your own data structures and server logic. * **Another MCP SDK.** There might be other, less common, MCP SDKs available. 2. **What kind of MCP server do you want to create?** What specific resources will it serve? For example: * **Route Configuration (RDS) server:** Serves route configurations to Envoy proxies. * **Cluster Configuration (CDS) server:** Serves cluster definitions to Envoy proxies. * **Listener Configuration (LDS) server:** Serves listener configurations to Envoy proxies. * **Endpoint Discovery Service (EDS) server:** Serves endpoint information to Envoy proxies. * **A custom resource server:** Serves your own custom resource types. 3. **What is your desired level of detail?** Do you want: * **A high-level overview of the process?** * **Example code snippets?** * **A complete, runnable example?** (This would be more complex and require more information from you.) **General Steps (Assuming Istio/Envoy MCP):** Here's a general outline of the steps involved in creating an MCP server using a TypeScript SDK (assuming it's based on the Envoy/Istio MCP protocol): 1. **Install the Necessary Packages:** You'll need to install the appropriate TypeScript packages. This will likely involve: * The core gRPC library for TypeScript (`@grpc/grpc-js` or similar). * The generated TypeScript code from the Protocol Buffers (`.proto`) definitions for the MCP resources you want to serve (e.g., `envoy.config.route.v3`, `envoy.config.cluster.v3`, etc.). You'll typically use `protoc` (the Protocol Buffer compiler) and a TypeScript plugin to generate these files. * Potentially, a library that provides helper functions for working with MCP. ```bash npm install @grpc/grpc-js google-protobuf # And potentially other packages depending on your setup ``` 2. **Generate TypeScript Code from Protocol Buffers:** You'll need to obtain the `.proto` files that define the MCP resources (e.g., from the `envoyproxy/go-control-plane` repository or your own custom definitions). Then, use `protoc` to generate TypeScript code from these files. This will create the TypeScript classes that represent the resource types. Example `protoc` command (you'll need to adjust this based on your `.proto` file locations and plugin configuration): ```bash protoc --plugin=protoc-gen-ts=./node_modules/.bin/protoc-gen-ts --ts_out=. your_mcp_resource.proto ``` 3. **Implement the gRPC Service:** Create a TypeScript class that implements the gRPC service defined in the `.proto` files. This class will have methods that correspond to the MCP endpoints (e.g., `StreamRoutes`, `StreamClusters`, etc.). These methods will receive requests from Envoy proxies and return the appropriate resource configurations. 4. **Handle the MCP Stream:** The core of an MCP server is handling the bidirectional gRPC stream. Your service implementation will need to: * Receive `DiscoveryRequest` messages from the client (Envoy proxy). * Process the request, determining which resources the client is requesting. * Fetch the appropriate resource configurations from your data store (e.g., a database, a configuration file, or in-memory data). * Construct `DiscoveryResponse` messages containing the resource configurations. * Send the `DiscoveryResponse` messages back to the client. * Handle errors and stream termination gracefully. 5. **Manage Resource Versions (Important for Updates):** MCP uses versioning to ensure that clients receive consistent updates. You'll need to track the versions of your resources and include them in the `DiscoveryResponse` messages. When a client sends a `DiscoveryRequest`, it will include the version of the resources it currently has. Your server should only send updates if the client's version is out of date. 6. **Implement a Data Store (Configuration Source):** You'll need a way to store and manage the resource configurations that your MCP server serves. This could be a simple configuration file, a database, or a more complex configuration management system. 7. **Start the gRPC Server:** Use the gRPC library to start a gRPC server and register your service implementation with it. The server will listen for incoming connections from Envoy proxies. 8. **Configure Envoy to Use Your MCP Server:** Configure your Envoy proxies to connect to your MCP server. This will typically involve specifying the server's address and port in the Envoy configuration. **Example (Conceptual - Requires Adaptation):** ```typescript // Assuming you've generated TypeScript code from your .proto files // import { RouteDiscoveryServiceService, RouteDiscoveryServiceHandlers } from './route_discovery_grpc_pb'; // import { DiscoveryRequest, DiscoveryResponse } from './discovery_pb'; import * as grpc from '@grpc/grpc-js'; // Replace with your actual generated code interface DiscoveryRequest { versionInfo: string; node: any; // Replace with your Node type resourceNames: string[]; typeUrl: string; responseNonce: string; errorDetail: any; // Replace with your Status type } interface DiscoveryResponse { versionInfo: string; resources: any[]; // Replace with your Resource type typeUrl: string; nonce: string; controlPlane: any; // Replace with your ControlPlane type } interface RouteDiscoveryServiceHandlers { streamRoutes: grpc.ServerDuplexStream<DiscoveryRequest, DiscoveryResponse>; } class RouteDiscoveryServiceImpl implements RouteDiscoveryServiceHandlers { streamRoutes(stream: grpc.ServerDuplexStream<DiscoveryRequest, DiscoveryResponse>): void { stream.on('data', (request: DiscoveryRequest) => { console.log('Received request:', request); // Fetch route configurations based on the request const routes = this.fetchRoutes(request); // Construct the DiscoveryResponse const response: DiscoveryResponse = { versionInfo: 'v1', // Replace with your versioning logic resources: routes, typeUrl: 'envoy.config.route.v3.RouteConfiguration', // Replace with your resource type URL nonce: 'some-nonce', // Generate a unique nonce controlPlane: null, // Replace if you have control plane info }; stream.write(response); }); stream.on('end', () => { console.log('Stream ended'); stream.end(); }); stream.on('error', (err) => { console.error('Stream error:', err); stream.end(); }); } private fetchRoutes(request: DiscoveryRequest): any[] { // Implement your logic to fetch route configurations // based on the request parameters (e.g., resourceNames, versionInfo) // This is where you would access your data store. console.log("fetching routes"); return [ { name: 'route1', domains: ['example.com'] }, { name: 'route2', domains: ['test.com'] }, ]; // Replace with actual route configurations } } function main() { const server = new grpc.Server(); // server.addService(RouteDiscoveryServiceService, new RouteDiscoveryServiceImpl()); server.addService({streamRoutes: {path: "/envoy.service.discovery.v3.RouteDiscoveryService/StreamRoutes", requestStream: true, responseStream: true, requestSerialize: (arg: any) => Buffer.from(JSON.stringify(arg)), requestDeserialize: (arg: Buffer) => JSON.parse(arg.toString()), responseSerialize: (arg: any) => Buffer.from(JSON.stringify(arg)), responseDeserialize: (arg: Buffer) => JSON.parse(arg.toString())}}, new RouteDiscoveryServiceImpl()); server.bindAsync('0.0.0.0:50051', grpc.ServerCredentials.createInsecure(), (err, port) => { if (err) { console.error('Failed to bind:', err); return; } console.log(`Server listening on port ${port}`); server.start(); }); } main(); ``` **Important Considerations:** * **Error Handling:** Implement robust error handling to gracefully handle unexpected situations. * **Logging:** Add logging to help you debug and monitor your MCP server. * **Security:** Secure your gRPC server using TLS/SSL. * **Scalability:** Consider the scalability of your MCP server, especially if you're serving a large number of Envoy proxies. * **Testing:** Thoroughly test your MCP server to ensure that it's working correctly. **Next Steps:** 1. **Tell me which MCP SDK you're using.** 2. **Tell me what kind of MCP server you want to create.** 3. **Tell me your desired level of detail.** Once I have this information, I can provide you with more specific and helpful guidance.