Discover Awesome MCP Servers

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.

Wave MCP Server

MCP server for Wave accounting that provides tools for managing chart of accounts, invoices, customers, vendors, products, and reports via the Wave GraphQL API.

Redfish MCP Server

Enables AI agents and LLMs to control and monitor Redfish-enabled hardware through power operations, system inventory, event logs, health monitoring, sensor readings, and user account management.

graphql-agent-toolkit

Enables AI agents to interact with any GraphQL API by introspecting the schema and exposing queries and mutations as MCP tools, with built-in pagination, semantic search, and framework adapters.

Amazon POE MCP Server

Extracts data from Amazon's Product Opportunity Explorer in Seller Central via browser automation, enabling niche search and CSV export of search terms, products, customer reviews, returns, and insights using natural language.

ClickUp MCP Server (Enhanced Fork)

Enables AI assistants to manage ClickUp tasks, dependencies, time tracking, documents, and workspace organization via natural language, with enhanced task dependency features and improved reliability.

Filesystem MCP

Here are a few ways to translate the English phrase "mcp server to modify files safely in a root directory where user should not be able to escape from" into Spanish, with slight variations in emphasis: * **Opción 1 (Más directa):** Servidor MCP para modificar archivos de forma segura en un directorio raíz del que el usuario no debería poder escapar. * **Opción 2 (Enfatizando la seguridad):** Servidor MCP para modificar archivos de manera segura en un directorio raíz, impidiendo que el usuario pueda salir de él. * **Opción 3 (Con un poco más de formalidad):** Servidor MCP para modificar archivos de forma segura dentro de un directorio raíz, restringiendo el acceso del usuario fuera de este. **Explanation of Choices:** * **Servidor MCP:** "MCP server" translates directly to "Servidor MCP." Assuming "MCP" is an acronym, it's best to leave it as is. * **Modificar archivos:** "Modify files" translates to "modificar archivos." * **De forma segura / De manera segura:** Both "de forma segura" and "de manera segura" are good translations for "safely." The choice is a matter of preference. * **Directorio raíz:** "Root directory" translates directly to "directorio raíz." * **Del que el usuario no debería poder escapar / Impidiendo que el usuario pueda salir de él / Restringiendo el acceso del usuario fuera de este:** These are all ways to express the idea of preventing the user from escaping the root directory. The first option is more literal, while the second and third options are slightly more descriptive. I would recommend **Opción 2** as it is clear and emphasizes the security aspect.

@shipeasy/mcp

A unified MCP server for experimentation and i18n, enabling AI assistants to manage feature flags, experiments, metrics, events, and string translations via natural language.

Playwright MCP

A server that provides browser automation capabilities using Playwright, enabling LLMs to interact with web pages through structured accessibility snapshots without requiring screenshots or vision models.

Vendor Risk Assessment MCP Server

Enables AI-powered vendor risk assessment using AWS Titan, allowing users to evaluate individual vendors, compare multiple vendors, and get industry risk benchmarks through natural language queries.

CLARA MCP Server

A hybrid pulmonary radiology diagnostic backend that provides MCP agent skills for vision inference, clinical RAG, report synthesis, and escalation, with multi-layer security.

Bilibili MCP

Enables searching for Bilibili videos through a standardized MCP interface, returning video information including title, author, view count, and duration with pagination support.

VideoGen Advisor

A unified MCP server for video generation that intelligently routes requests to HeyGen (for avatar/presenter videos) or Google Veo (for creative/cinematic content).

ucon-mcp

Verified unit conversion and dimensional analysis for AI agents. 190+ units, 31 domain formulas (clinical, physics, aerospace, SRE), physical constants with uncertainty propagation. Refuses invalid conversions structurally: the tool that won't convert mg to mL and knows the difference between torque and energy.

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!

DeFi Trading Agent MCP Server

Transforms AI assistants into autonomous crypto trading agents with real-time market analysis, portfolio management, and trade execution across 17+ blockchains.

PCAP-Analyzer MCP Server

Enables natural language analysis of network packet captures, including protocol detection, flow analysis, and security threat identification, integrated with AI assistants.

Casper Network MCP Server

Enables interaction with the Casper Network blockchain via MCP, providing tools for wallet creation, CSPR transfers, staking/delegation, and account queries.

Metacognitive Compute Scheduler

An MCP server that decides whether each step of an agent requires cheap intuition (System 1) or expensive deliberation (System 2) by learning from experience rather than hand-written rules.

Motor Agéntico Plugin MCP

Enables scaffolding, validating, and managing plugins for the Motor Agéntico ecosystem, with tools to generate plugin structures and verify compliance with the plugin standard.

booking-mcp

MCP server exposing a PostgreSQL booking datastore to MCP clients, enabling read/write operations on staff, schedules, clients, and bookings with optional human-approval workflow integration.

McpLLMServer

A FastAPI-based MCP server that enables LLM agents to interact with Ollama models through standardized MCP tools, with optional MySQL and Redis integration for data persistence and caching.

notebooklm-mcp

Bridges Claude Code/Cowork with Google NotebookLM for AI-powered research, source analysis, chat, and content generation through a structured tool interface.

MCP Midjourney

Enables AI image and video generation using Midjourney through the AceDataCloud API. It supports comprehensive features including image creation, transformation, blending, editing, and video generation directly within MCP-compatible clients.

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.

swarm-mcp

An MCP server that provides access to Foursquare Swarm check-in data, enabling AI assistants to query check-in history, stats, top venues, and venue details.

scheduler-mcp

Self-hosted scheduler using Notion as control plane and Docker container with SQLite ledger, executing scheduled notifications, scripts, and LLM agents with MCP tools.

playcaller

An MCP server that enables AI agents to play-test Unity games by capturing screenshots and simulating inputs like taps, drags, and key presses, acting as a Playwright for Unity.

logseq-api-mcp

AI assistant integration with Logseq knowledge graph: 21 tools to read, write, query, and search notes, enabling seamless interaction with your notes.

question-market

MCP server for question.market prediction markets on Algorand. Enables market browsing, wallet onboarding, and trading through natural language.