Discover Awesome MCP Servers

Screen Agent

A Windows desktop automation MCP server that enables UI recognition through OCR, UIA controls, and multi-point color matching. It allows agents to interact with desktop applications via actions like clicking and typing while using a learning system to track and improve operation success.

Medicare MCP Server

Provides comprehensive access to CMS Medicare data including physician services, prescriber information, hospital quality metrics, drug spending, formulary coverage, and ASP pricing for healthcare analysis and decision-making.

macOS Tools MCP Server

Provides read-only access to native macOS system utilities including disk management, battery status, network configuration, and system profiling through terminal commands. Enables users to retrieve system information and diagnostics from macOS machines via standardized MCP tools.

Docker MCP Server

Enables AI assistants to interact with Docker containers through safe, permission-controlled access to inspect, manage, and diagnose containers, images, and compose services with built-in timeouts and AI-powered analysis.

Datastream MCP Server

A Multi-Agent Conversation Protocol server that enables interaction with Google Cloud Datastream API for managing data replication services between various source and destination systems through natural language commands.

AutoSOC Agent

An automated security operations center MCP server that uses LLMs and network analysis tools like Tshark to detect threats in traffic data. It enables users to automatically ingest PCAP files, query specific packets, and generate intelligent security analysis reports.

MCP Sample Server

A simple Model Context Protocol server providing basic utility tools including timezone-aware time retrieval and basic arithmetic calculations (add, subtract, multiply, divide).

Pagila MCP

A read-only Model Context Protocol server developed with FastMCP for querying the Pagila PostgreSQL database. It enables secure access to movie rental data including films, actors, and customer information through natural language queries.

OfficeRnD MCP Server

A read-only MCP server that connects AI assistants to the OfficeRnD coworking and flex-space management platform. It enables natural language queries for community members, space bookings, billing records, and office resources.

PDFSizeAnalyzer-MCP

Enables comprehensive PDF analysis and manipulation including page size analysis, chapter extraction, splitting, compression, merging, and conversion to images. Provides both MCP server interface for AI assistants and Streamlit web interface for direct user interaction.

mcp-altegio

MCP server for Altegio API — appointments, clients, services, staff schedules

database-updater MCP Server

Espejo de

MCP Servers

Una colección de servidores MCP (Protocolo de Contexto de Modelo) como herramientas de dotnet.

HashiCorp Vault MCP Server

Enables interaction with HashiCorp Vault for secret management operations including reading, writing, listing, and deleting secrets through the Model Context Protocol.

Google Search MCP Server

Una implementación de servidor MCP que se integra con la API JSON de Búsqueda Personalizada de Google, proporcionando capacidades de búsqueda web.

Pytest MCP Server

Enables AI assistants to run and analyze pytest tests for desktop applications through interactive commands. Supports test execution, filtering, result analysis, and debugging for comprehensive test automation workflows.

flutterclimcp

Okay, here's a fun Flutter project idea that leverages the Flutter CLI and a hypothetical "MCP (Model Context Protocol) Server" for a more dynamic and data-driven development experience. I'll outline the project, explain how the MCP Server *could* be used, and provide some example Flutter CLI commands. **Project Idea: "Dynamic Recipe App"** This app will display recipes fetched from a hypothetical MCP Server. The MCP Server will allow you to easily update the recipes without needing to redeploy the Flutter app. Think of it as a lightweight CMS specifically designed to feed data to your Flutter app. **Core Features:** * **Recipe Listing:** Displays a list of recipe titles and brief descriptions. * **Recipe Detail View:** Shows the full recipe, including ingredients, instructions, and potentially images. * **Dynamic Updates:** The app automatically reflects changes made to the recipes on the MCP Server (e.g., new recipes, updated ingredients). * **Search/Filtering (Optional):** Allow users to search for recipes by name or filter by ingredients. * **User Ratings/Reviews (Optional):** Allow users to rate and review recipes. **How the Hypothetical MCP Server Would Work (Conceptual):** The MCP Server would expose an API (likely REST or GraphQL) that allows you to: * **Define Data Models:** Specify the structure of a recipe (e.g., title, description, ingredients, instructions, image URL). * **Manage Data:** Create, read, update, and delete recipes. * **Provide Data Context:** The server would provide the data in a structured format that the Flutter app can easily consume. This is where the "Context" part of MCP comes in. It provides the data *and* the metadata about the data. **Flutter CLI Commands (Example):** 1. **Create a New Flutter Project:** ```bash flutter create dynamic_recipe_app cd dynamic_recipe_app ``` 2. **Add Dependencies:** You'll need `http` for making API requests and potentially `cached_network_image` for efficient image loading. You might also want a state management solution like Provider, Riverpod, or BLoC. ```bash flutter pub add http flutter pub add cached_network_image flutter pub add provider # Or your preferred state management ``` 3. **Generate Initial UI (Using Flutter CLI - Hypothetical MCP Integration):** *This is where the MCP integration would be really cool. Imagine a command that could scaffold basic UI elements based on the data model defined on the MCP Server.* ```bash # Hypothetical command: flutter mcp generate ui --model recipe --output lib/screens/recipe_list.dart flutter mcp generate ui --model recipe --output lib/screens/recipe_detail.dart --detail ``` * This command *doesn't exist* in the standard Flutter CLI. It's an example of how the CLI *could* be extended to work with an MCP Server. It would generate basic Flutter code for displaying a list of recipes and a detailed view of a single recipe, based on the `recipe` model defined on the MCP Server. 4. **Run the App:** ```bash flutter run ``` **Flutter Code Structure (Example - Without Hypothetical CLI):** Since the `flutter mcp generate ui` command is hypothetical, you'll need to write the UI code manually. Here's a basic structure: * `lib/main.dart`: The entry point of your app. Sets up the MaterialApp and initial route. * `lib/models/recipe.dart`: Defines the `Recipe` class (e.g., `title`, `description`, `ingredients`, `instructions`, `imageUrl`). * `lib/screens/recipe_list.dart`: Fetches the list of recipes from the MCP Server and displays them in a `ListView`. * `lib/screens/recipe_detail.dart`: Displays the details of a single recipe. * `lib/services/api_service.dart`: Handles the HTTP requests to the MCP Server. This class would have methods like `getRecipes()` and `getRecipe(int id)`. * `lib/widgets/recipe_card.dart`: A reusable widget to display a recipe in the list. **Example `lib/services/api_service.dart` (Illustrative):** ```dart import 'dart:convert'; import 'package:http/http.dart' as http; import 'package:dynamic_recipe_app/models/recipe.dart'; // Assuming you have a Recipe model class ApiService { final String baseUrl = 'YOUR_MCP_SERVER_URL'; // Replace with your MCP server URL Future<List<Recipe>> getRecipes() async { final response = await http.get(Uri.parse('$baseUrl/recipes')); if (response.statusCode == 200) { List<dynamic> body = jsonDecode(response.body); List<Recipe> recipes = body.map((dynamic item) => Recipe.fromJson(item)).toList(); return recipes; } else { throw Exception('Failed to load recipes'); } } Future<Recipe> getRecipe(int id) async { final response = await http.get(Uri.parse('$baseUrl/recipes/$id')); if (response.statusCode == 200) { Map<String, dynamic> body = jsonDecode(response.body); Recipe recipe = Recipe.fromJson(body); return recipe; } else { throw Exception('Failed to load recipe'); } } } ``` **Key Considerations:** * **State Management:** Choose a state management solution (Provider, Riverpod, BLoC) to handle the data flow and updates in your app. This is crucial for reflecting changes from the MCP Server. * **Error Handling:** Implement proper error handling for API requests. * **Loading Indicators:** Show loading indicators while data is being fetched from the MCP Server. * **Real-time Updates (Optional):** For true real-time updates, you could explore using WebSockets or Server-Sent Events (SSE) with your MCP Server. This would allow the server to push updates to the app whenever a recipe is changed. * **Security:** If your MCP Server requires authentication, implement appropriate authentication mechanisms in your Flutter app. **Why This is a Fun Project:** * **Dynamic Content:** You can update the app's content without redeploying the app. * **Backend Integration:** It involves integrating with a backend API, which is a common task in real-world app development. * **Scalability:** The MCP Server concept allows you to easily scale the content of your app. * **Learning Opportunity:** You'll learn about HTTP requests, JSON parsing, state management, and potentially real-time communication. * **Hypothetical CLI Extension:** Thinking about how the Flutter CLI could be extended to work with an MCP Server is a great exercise in understanding the Flutter ecosystem and potential future improvements. **To make this project real, you would need to:** 1. **Build the MCP Server:** This is the most significant part. You could use Node.js with Express, Python with Flask or Django, or any other backend technology you're comfortable with. The server needs to expose an API for managing recipes. 2. **Implement the Flutter App:** Write the Flutter code to fetch data from the MCP Server and display it in the UI. This project provides a solid foundation for building a dynamic and data-driven Flutter application. Remember to replace `YOUR_MCP_SERVER_URL` with the actual URL of your MCP server. Good luck!

mcp-lucene-server

mcp-lucene-server

Python Code Runner

Enables execution of Python code in a safe environment, including running scripts, installing packages, and retrieving variable values. Supports file operations and package management through pip.

MCP Servers

Open Source MCP Servers for Scientific Research

Web Crawler MCP Server

An intelligent web crawling server that uses Cloudflare's headless browser to render dynamic pages and Workers AI to extract relevant links based on natural language queries. It enables AI assistants to search and filter website content while providing secure access through GitHub OAuth authentication.

Google Tag Manager MCP Server

Integrates Google Tag Manager with Claude to automate the creation and management of tags, triggers, and variables using natural language prompts. It provides specialized tools for GA4 and Facebook Pixel setup, along with automated tracking workflows for ecommerce and lead generation sites.

Advanced MCP Server

A comprehensive Model Context Protocol server providing capabilities for web scraping, data analysis, system monitoring, file operations, API integrations, and report generation.

MCPHub: Deploy Your Own MCP Servers in Minutes

A unified hub server that consolidates multiple MCP servers into one single SSE endpoint

AI-Scholarly-Mode

Enables AI assistants to search and retrieve peer-reviewed academic articles exclusively from Springer Nature's open access collection. It provides a specialized mode for research-driven conversations, allowing users to toggle scholarly-only search and fetch full article content.

ShopOracle

E-Commerce Intelligence MCP Server — 11 tools for product search, price comparison, competitor pricing across Amazon, eBay, Google Shopping. 18 countries. Part of ToolOracle (tooloracle.io).

MCP Memory

Enables AI assistants to remember user information and preferences across conversations using vector search technology. Built on Cloudflare infrastructure with isolated user namespaces for secure, persistent memory storage.

XRootD MCP Server

An MCP server providing access to XRootD file systems, allowing LLMs to browse directories, read file metadata, and access contents via the root:// protocol. It supports advanced features like campaign discovery, file searching, and ROOT file analysis for scientific data management.

Jira Prompts MCP Server

Un servidor MCP que ofrece varios comandos para generar prompts o contextos a partir del contenido de Jira.

Knowledge Graph Memory Server

Una implementación mejorada de memoria persistente que utiliza un grafo de conocimiento local con una opción `--memory-path` personalizable. Esto permite que Claude recuerde información sobre el usuario entre chats.