MCP Gateway – API & Portal de Autoatendimento

Overview: What is MCP Gateway?

The MCP Gateway is an essential component in the Model Context Protocol (MCP) ecosystem, designed to expose and manage internal tools (APIs) for secure, scalable, and auditable access. It leverages Role-Based Access Control (RBAC) and JWT authentication to ensure only authorized users can access specific functionalities. This gateway serves as a crucial bridge between AI applications like Claude Desktop, Continue, Cursor, and other MCP clients, enabling seamless integration with various data sources and tools.

🔧 Core Features & MCP Capabilities

Backend Integration

The backend of the MCP Gateway is built using FastAPI, providing robust and efficient API management. It includes authentication mechanisms such as JWT (JSON Web Tokens) for secure user sessions and RBAC (Role-Based Access Control) to manage permissions at different levels. The server can persist data in a JSON format, making it easy to integrate with NoSQL databases if needed.

Frontend Integration

The frontend is developed using React (with Vite), creating an intuitive portal that allows users to interact with the tools exposed through the backend API. This integration ensures a seamless user experience and provides comprehensive management capabilities for groups, users, and tools.

The gateway supports multiple operational modes: development (with auto-reloading) and production (where the frontend is built separately). This dual-mode operation ensures flexibility in both testing and deployment environments.

Key Functionalities

• User Authentication: Supports JWT tokens for user sessions.
• RBAC Management: Enables fine-grained permission management with hierarchical group structures.
• Tool Registration & Dynamic Creation: Admins can manage and dynamically register new tools through the management interface.
• Portal Access: Provides a secure portal for users to access registered tools.
• Healthcheck & Logging: Monitors server health and logs actions efficiently.
• Automatic Documentation: Integrates with Swagger UI for automatic API documentation.

MCP Client Compatibility

The MCP Gateway is compatible with various AI clients, including:

• Claude Desktop: Full support for all resources, tools, and prompts.
• Continue: Compatible with most features, focusing on tools and resource management.
• Cursor: Limited support, focusing primarily on tools.

⚙️ MCP Architecture & Protocol Implementation

The architecture of the MCP Gateway is modular, consisting of distinct components that handle different aspects of the system:

Backend Structure

• app/: Houses the main FastAPI application along with configuration and authentication modules.
• data/: Stores persistent data like RBAC configurations in JSON format.
• frontend/: Contains the React frontend source code for the portal.
• requirements.txt: Lists all necessary Python dependencies.

The backend is responsible for handling API requests, managing user sessions, and integrating tools. The frontend provides a user-friendly interface for interacting with these APIs.

Frontend Structure

The frontend is built using Vite, which allows hot reloading during development. It serves as the primary interface through which users interact with the exposed tools.

🚀 Getting Started with Installation

To get MCP Gateway running on your local machine, follow these steps:

1. Backend (FastAPI) Installation:

   python -m venv venv
   .\venv\Scripts\activate
   pip install -r requirements.txt
   uvicorn app.main:app --reload
   

2. Frontend (React) Installation:

   cd frontend
   npm install
   npm run dev
   

Access the portal by navigating to http://localhost:5173 for development purposes, or http://localhost:8000 for production.

Production Build of Frontend:

cd frontend
npm run build

This will generate the frontend/dist folder which can be served by the FastAPI server if desired.

💡 Key Use Cases in AI Workflows

Case 1: Data Analysis Workflow

An AI analyst uses Claude Desktop to conduct data analysis. They connect to a PostgreSQL database via an MCP Gateway endpoint that has been configured with permission levels for reading, writing, and executing queries. The analyst creates an interactive dashboard using the PostgreSQL tool, retrieving and visualizing data in real time.

Case 2: Chatbot Integration

A company uses Continue as its AI chatbot solution. They integrate this tool via an MCP Gateway endpoint that has access to customer support tickets stored in a NoSQL database. The chatbot can now pull these tickets, analyze them, and provide relevant responses to customer inquiries efficiently.

🔌 Integration with MCP Clients

The MCP Gateway supports multiple clients, ensuring seamless interaction between different AI tools:

• Claude Desktop: Full integration, enabling data access, tool usage, and customization.
• Continue: Limited integration, focusing on resource management and tool operations.
• Cursor: Minimal support, primarily for tool integration.

📊 Performance & Compatibility Matrix

Here is a compatibility matrix showing the status of different MCP clients with the gateway:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

🛠️ Advanced Configuration & Security

The server includes several key security features:

• JWT Authentication: Ensures secure user sessions.
• RBAC Management: Provides granular permission management through roles and groups.
• Logging & Healthcheck: Monitors system health and logs actions for auditing.

Configuration settings are stored in the config.py file within the backend module. Example configuration code:

{
  "mcpServers": {
    "[server-name]": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-[name]"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

❓ Frequently Asked Questions (FAQ)

1. Q: How do I integrate my AI application with the MCP Gateway?
   • A: Use the provided API endpoints and JWT authentication to securely connect your AI client.
2. Q: Can multiple clients use this server simultaneously?
   • A: Yes, the gateway is designed to support multiple concurrent connections from various MCP clients.
3. Q: How do I manage user permissions in the Gateway?
   • A: RBAC (Role-Based Access Control) allows you to define roles and assign permissions at different levels within groups.
4. Q: Is there built-in logging for troubleshooting issues?
   • A: Yes, comprehensive logging is enabled out-of-the-box for auditing purposes.
5. Q: Can I deploy the Gateway in a production environment?
   • A: Absolutely, the gateway supports both development and production environments with optional frontend build steps.

👨‍💻 Development & Contribution Guidelines

To contribute to or develop this MCP server further:

• Keep Python dependencies updated using pip.
• Use virtual environments for Python.
• Always generate a production build of the frontend before deploying in production.
• Refer to additional documentation located in the docs/ directory.

🌐 MCP Ecosystem & Resources

The MCP Gateway is part of a broader ecosystem of tools and resources aimed at enhancing AI application integration. The official documentation, including detailed guidelines and examples, can be found here:

• Official Documentation: Link
• API Reference: Link
• User Guide: Link

MCP Protocol Flow Diagram

Below is the flow diagram for the Model Context Protocol (MCP):

graph TD
    A[AI Application] -->|MCP Client| B[MCP Server]
    B --> C[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5

MCP Configuration Code Sample

{
  "mcpServers": {
    "[server-name]": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-[name]"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

This sample demonstrates how to configure an MCP client connection within the gateway.

By providing extensive documentation and configuration examples, this MCP Gateway serves as a robust foundation for building integrations between AI applications and data sources, ensuring seamless and secure access management.