Discover Awesome MCP Servers

Magic Component Platform

Ferramenta baseada em IA que ajuda desenvolvedores a criar componentes de UI bonitos instantaneamente através de descrições em linguagem natural, integrando-se com IDEs populares como Cursor, Windsurf e VSCode.

WooCommerce MCP Server

Enables interaction with WooCommerce stores through the WordPress REST API, supporting comprehensive management of products, orders, customers, shipping, taxes, discounts, and store configuration.

mcp-talib

Um servidor de Protocolo de Contexto de Modelo (MCP) que fornece as funções do ta-lib-python.

MCP Prompt Manager

Git-driven MCP server that manages and provides prompt templates with Handlebars support, enabling teams to collaborate on and version-control reusable, dynamic prompts across AI editors like Cursor and Claude Desktop.

MCP Security Scanner

Automatically discovers and tests MCP services for security vulnerabilities including command injection, SQL injection, SSRF, path traversal, and sensitive data exposure with detailed reports and remediation guidance.

Doxygen MCP Server

A comprehensive server that enables AI assistants to generate, configure, and manage Doxygen documentation for various programming languages through a clean interface.

AdsPower LocalAPI MCP Server

A Model Context Protocol server that enables LLMs to interact with AdsPower browser LocalAPI, allowing for operations like creating, opening, updating, and managing browser profiles with custom fingerprints.

Geekbot MCP

Um servidor que conecta a IA Claude da Anthropic com as ferramentas de gestão de stand-up do Geekbot, permitindo que os usuários acessem e utilizem dados do Geekbot dentro das conversas do Claude.

Job Search MCP Server

Enables searching for AI/ML internships and entry-level positions across multiple job sites including LinkedIn, Indeed, Glassdoor, ZipRecruiter, and Monster. Automatically filters for Python proficiency and relevant AI/ML skills while providing structured job data with application URLs and detailed requirements.

dv-flow-mcp

Servidor de Protocolo de Contexto do Modelo (MCP) para DV Flow

Joern MCP Server

A simple MCP (Multimodal Conversational Plugin) server based on Joern that provides code review and security analysis capabilities through natural language interfaces.

PowerPoint Translator MCP Service

Enables translation of PowerPoint presentations to multiple languages using AWS Bedrock models while preserving formatting. Supports 8 languages including Chinese, Japanese, Korean, and major European languages.

PDF MCP Server

An MCP server for PDF form filling, basic editing, and OCR text extraction. It enables users to merge, rotate, annotate, and sign PDFs, while also supporting text extraction from both searchable and scanned image-based documents.

Japanese Character Counter MCP Server

Accurately counts Japanese text characters using grapheme clusters, properly handling surrogate pairs and combining characters through the Intl.Segmenter API.

Todoist MCP Server Extended

Enables natural language task management with Todoist, supporting tasks, projects, sections, labels, smart search, and batch operations for efficient workflow integration with Claude and other MCP-compatible LLMs.

Scanpy-MCP

Provides a natural language interface for scRNA-Seq analysis using the Scanpy library, supporting operations such as data preprocessing, clustering, and visualization. It enables AI agents and clients to perform complex single-cell transcriptomics workflows through the Model Context Protocol.

MySQL MCP Server

Provides AI assistants with secure read-only access to MySQL databases through validated SELECT queries. Supports SSL/TLS connections and implements multiple security layers to prevent data modification.

Conduit

AI-powered connection manager with 60+ MCP tools for SSH terminal execution, RDP desktop control, VNC interaction, web session automation, and encrypted credential vault management. Works with Claude Code, Cursor, Windsurf, and any MCP-compatible client.

MCP Server for Awesome-llms-txt

Okay, I understand. You want me to create an MCP (presumably referring to a "Minimal, Complete, and Verifiable" example) server setup for the `SecretiveShell/Awesome-llms-txt` project, and to document the process directly within this conversation, using MCP resources. This is a bit abstract, as I don't have direct access to your file system or the `SecretiveShell/Awesome-llms-txt` project. Therefore, I'll provide a *conceptual* MCP, focusing on the core elements and assuming a basic understanding of Python and server setup. You'll need to adapt this to your specific environment and project structure. **Conceptual MCP: A Simple API Server for Serving Text from `Awesome-llms-txt`** This MCP will focus on: 1. **Loading Text Data:** How to load text data from a file (assuming `Awesome-llms-txt` contains text files). 2. **A Minimal API Endpoint:** A single API endpoint that returns the content of a specific text file. 3. **Basic Server Setup (using Flask):** A simple Flask server to host the API. 4. **Documentation within the Code:** Docstrings and comments to explain the code. **Code (Python with Flask):** ```python from flask import Flask, jsonify, abort import os app = Flask(__name__) # --- Configuration --- TEXT_DIRECTORY = "path/to/your/Awesome-llms-txt/text_files" # Replace with the actual path ALLOWED_EXTENSIONS = ['.txt'] # --- Helper Functions --- def is_valid_file(filename): """ Checks if a filename is valid based on allowed extensions. Args: filename (str): The name of the file. Returns: bool: True if the file is valid, False otherwise. """ return any(filename.endswith(ext) for ext in ALLOWED_EXTENSIONS) def load_text_file(filename): """ Loads the content of a text file. Args: filename (str): The name of the file to load. Returns: str: The content of the file, or None if the file doesn't exist or is invalid. """ filepath = os.path.join(TEXT_DIRECTORY, filename) if not os.path.exists(filepath) or not is_valid_file(filename): return None try: with open(filepath, 'r', encoding='utf-8') as f: return f.read() except Exception as e: print(f"Error reading file: {e}") # Log the error return None # --- API Endpoints --- @app.route('/text/<filename>', methods=['GET']) def get_text(filename): """ API endpoint to retrieve the content of a text file. Args: filename (str): The name of the text file to retrieve. Returns: JSON: A JSON response containing the text content, or an error message. """ text_content = load_text_file(filename) if text_content is None: abort(404, description="File not found or invalid.") # Return a 404 error return jsonify({'filename': filename, 'content': text_content}) # --- Error Handling --- @app.errorhandler(404) def resource_not_found(e): """ Custom error handler for 404 errors. """ return jsonify(error=str(e)), 404 # --- Main Execution --- if __name__ == '__main__': app.run(debug=True) # Enable debug mode for development ``` **Explanation and Documentation (MCP Resources):** * **`TEXT_DIRECTORY`:** This variable *must* be updated to point to the actual directory where your text files from `Awesome-llms-txt` are located. This is crucial. * **`ALLOWED_EXTENSIONS`:** This list defines the file extensions that are considered valid. Adjust this if your files have different extensions. * **`is_valid_file(filename)`:** This function checks if a given filename is allowed based on its extension. This is a basic security measure to prevent arbitrary file access. * **`load_text_file(filename)`:** This function attempts to load the content of a text file. It handles file existence checks, extension validation, and potential file reading errors. The `encoding='utf-8'` is important for handling various character sets. Error handling is included to log potential issues. * **`@app.route('/text/<filename>', methods=['GET'])`:** This defines the API endpoint. The `<filename>` part is a variable that will be passed to the `get_text` function. The `methods=['GET']` specifies that this endpoint only accepts GET requests. * **`get_text(filename)`:** This function is the handler for the API endpoint. It calls `load_text_file` to retrieve the content of the specified file. If the file is not found or invalid, it returns a 404 error. Otherwise, it returns a JSON response containing the filename and the text content. * **`@app.errorhandler(404)`:** This defines a custom error handler for 404 errors. It returns a JSON response with an error message, which is generally better than the default HTML error page. * **`app.run(debug=True)`:** This starts the Flask development server. `debug=True` enables debug mode, which provides more detailed error messages and automatically reloads the server when you make changes to the code. **Do not use `debug=True` in a production environment.** **How to Run:** 1. **Install Flask:** `pip install Flask` 2. **Save the code:** Save the code above as a Python file (e.g., `api_server.py`). 3. **Update `TEXT_DIRECTORY`:** Modify the `TEXT_DIRECTORY` variable to point to the correct location of your text files. 4. **Run the server:** `python api_server.py` **Testing the API:** Once the server is running, you can test the API by opening a web browser or using a tool like `curl` and navigating to: `http://127.0.0.1:5000/text/your_file.txt` Replace `your_file.txt` with the actual name of a text file in your `TEXT_DIRECTORY`. **Example using `curl`:** ```bash curl http://127.0.0.1:5000/text/example.txt ``` **JSON Response (Success):** ```json { "filename": "example.txt", "content": "This is the content of example.txt." } ``` **JSON Response (Error - File Not Found):** ```json { "error": "404: File not found or invalid." } ``` **Important Considerations (Beyond the MCP):** * **Security:** This is a *very* basic example and is not secure for production use. You'll need to implement proper authentication, authorization, and input validation. * **Error Handling:** The error handling is minimal. You should add more robust error logging and reporting. * **Scalability:** Flask's built-in development server is not suitable for production. You'll need to use a production-ready WSGI server like Gunicorn or uWSGI. * **Configuration:** Hardcoding the `TEXT_DIRECTORY` is not ideal. You should use environment variables or a configuration file. * **Data Validation:** You might want to add more sophisticated data validation to ensure that the text files are in the expected format. * **Rate Limiting:** Implement rate limiting to prevent abuse. * **CORS:** If your frontend is hosted on a different domain, you'll need to configure CORS (Cross-Origin Resource Sharing). **MCP Principles Applied:** * **Minimal:** The code is as short and simple as possible while still demonstrating the core functionality. * **Complete:** The code includes all the necessary parts to run a basic API server. * **Verifiable:** You can copy and paste the code, install Flask, update the `TEXT_DIRECTORY`, and run the server to verify that it works. This MCP provides a starting point for building a more complex API server for your `Awesome-llms-txt` project. Remember to adapt it to your specific needs and to address the security and scalability considerations mentioned above. Let me know if you have any specific questions about any of these aspects.

Mixpanel MCP Connector

Enables ChatGPT to query and analyze Mixpanel analytics data in real-time. Provides live access to event segmentation and detailed analytics data from your Mixpanel project through natural language.

Vault MCP Bridge

Enables secure management of agent-scoped secrets in HashiCorp Vault through MCP protocol. Provides per-agent namespacing, multiple authentication methods (API key, JWT, mTLS), and optional encryption/decryption capabilities with built-in rate limiting.

Email MCP

Um servidor MCP que habilita a funcionalidade POP3 e SMTP para Agentes de IA compatíveis.

Modular MCP Server

A config-driven, zero-dependency MCP server with plugin architecture that enables filesystem operations, shell commands, HTTP requests, and utilities through simple JSON configuration.

RedNote MCP

Enables users to search and retrieve content from Xiaohongshu (Red Book) platform with smart search capabilities and rich data extraction including note content, author information, and images.

Quran Cloud MCP Server

Connects LLMs to the Quran API (alquran.cloud) to retrieve accurate Quranic text on-demand, reducing hallucinations when working with sensitive religious content.

MCP Voice Notification

Provides voice notifications using Grok's text-to-speech API to alert users when Claude Code completes tasks, with support for both local and remote server configurations.

view-image-mcp

Enables Claude Code to display images inline within supported terminals like Ghostty and Kitty using the Kitty graphics protocol on macOS. It allows users to view various image formats including PNG, JPEG, GIF, and WebP directly in the terminal interface.

task-orchestrator-mcp

An MCP server for task orchestration.

monarch-mcp-server

MCP Server for Monarch Money, utilizing an unofficial api.