AI Agent with MCP Tools and RBAC

A production-ready AI Agent system that combines the Model Context Protocol (MCP), LangChain ReAct Agent, and Role-Based Access Control (RBAC) using PyCasbin. This application demonstrates secure AI agent operations with enterprise-grade permission management.

Overview

This application implements a document management system where users with different roles (Admin, Editor, Viewer) interact with an AI agent. The agent autonomously selects and executes tools based on natural language queries, with all operations protected by RBAC policies.

Key Features

• MCP Protocol: HTTP + Server-Sent Events (SSE) for efficient communication
• RBAC Control: PyCasbin-based permission management
• LangChain Integration: ReAct Agent with OpenAI GPT-4o
• Enterprise UI: Modern, clean interface built with React and TailwindCSS
• Real-time Updates: Live document management and permission enforcement
• Security: Multi-layer defense with logging and audit trails

System Architecture

User Interface (React)
         ↓
   API Server (FastAPI)
         ↓
LangChain ReAct Agent (GPT-4o)
         ↓
   MCP Client (HTTP + SSE)
         ↓
   MCP Server (FastAPI)
         ↓
  RBAC Manager (PyCasbin) + Document Storage

Role Permissions

Role	Create	Read	Update	Delete
Admin	✅	✅	✅	✅
Editor	✅	✅	✅	❌
Viewer	❌	✅	❌	❌

Default Users

• alice (Admin): Full access to all operations
• bob (Editor): Can create, read, and update documents
• charlie (Viewer): Read-only access

Installation

1. Clone and Setup Environment

git clone https://github.com/AIAnytime/AI-Agent-with-MCP-Tools.git
cd AI-Agent-with-MCP-Tools
cd backend
activate .venv

2. Install Python Dependencies

pip install -r requirements.txt

3. Configure Environment Variables

The .env file should contain:

OPENAI_API_KEY=your_openai_api_key_here

4. Install Frontend Dependencies

cd frontend
npm install
cd ..

Running the Application

Option 1: Start All Services at Once (Recommended)

chmod +x start_all.sh
./start_all.sh

This will start:

• MCP Server on http://localhost:8765
• API Server on http://localhost:8000
• Frontend on http://localhost:3000

Usage

1. Open the application at http://localhost:3000

2. Select a user from the User Selector (alice, bob, or charlie)

3. Chat with the AI Agent using natural language:

   • "Create a document called 'project-plan' with content 'Q4 Project Planning'"
   • "List all documents"
   • "Read the document 'project-plan'"
   • "Update document 'project-plan' with new content"
   • "Delete the document 'project-plan'"
   • "Check my permissions"

4. View Documents in the Documents tab to see all created documents

5. Check Permissions in the Permissions tab to see the RBAC matrix

6. Learn About the System in the System Architecture tab

Example Demonstrations

Admin User (alice) - Full Access

Query: "Create a document called 'quarterly-report' with content 'Q4 2024 Report'"
Result: ✅ Document created successfully

Query: "Delete the document 'quarterly-report'"
Result: ✅ Document deleted successfully

Editor User (bob) - No Delete Permission

Query: "Create a document called 'meeting-notes' with content 'Team Meeting Notes'"
Result: ✅ Document created successfully

Query: "Delete the document 'meeting-notes'"
Result: ❌ Permission denied: Editor role cannot delete documents

Viewer User (charlie) - Read Only

Query: "Read the document 'meeting-notes'"
Result: ✅ Document content displayed

Query: "Update document 'meeting-notes' with 'Updated Notes'"
Result: ❌ Permission denied: Viewer role cannot update documents

Project Structure

mcp-rbac-app/
├── backend/
│   ├── api/
│   │   └── main.py              # FastAPI backend for frontend
│   ├── agent/
│   │   └── langchain_agent.py   # LangChain ReAct Agent
│   ├── mcp/
│   │   ├── mcp_server.py        # MCP HTTP Server
│   │   ├── mcp_client.py        # MCP Client
│   │   └── document_tools.py    # Document CRUD tools
│   ├── rbac/
│   │   ├── model.conf           # Casbin RBAC model
│   │   ├── policy.csv           # Casbin policies
│   │   └── rbac_manager.py      # RBAC enforcement
│   └── storage/
│       └── document_storage.py  # Document persistence
├── frontend/
│   ├── src/
│   │   ├── components/          # React components
│   │   ├── api/                 # API client
│   │   ├── App.jsx              # Main app component
│   │   └── main.jsx             # Entry point
│   ├── package.json
│   └── vite.config.js
├── data/
│   └── documents/               # Document storage (auto-created)
├── .env                         # Environment variables
├── requirements.txt