Multi-Agent-System-using-LangGraph-MCP-Supervisor-Guardrails-HITL

# Multi-Agent-System-using-LangGraph-MCP-Supervisor-Guardrails-HITL A demo multi-agent system that uses LangGraph and MCP to implement a travel-planning assistant with a Supervisor, input Guardrails, and Human-In-The-Loop (HITL) approval flows. The project includes a FastAPI frontend, example MCP server, and client helpers to demonstrate how agents, supervisors, and guardrails can be composed into a safe, reviewable planning pipeline. Key ideas: - Multi-agent coordination using LangGraph and MCP - Supervisor agent to manage complex workflows - Input guardrails to validate user requests - Human-in-the-loop approval for generated plans Contents - `app.py`: FastAPI web frontend and API endpoints - `backend.py`: core agent orchestration / travel-planner logic - `mcp_client.py`: client helpers to interact with the MCP server - `custom_weather_mcp_server.py`: example MCP server for weather checks - `templates/`, `static/`: frontend UI assets (HTML, JS, CSS) Features - Interactive web UI for sending travel planning prompts - Endpoint for drafting travel plans and separate approval endpoint - Example MCP server demonstrating domain adapters (weather, checkpoints) Prerequisites - Python 3.10+ (recommended) - Git (to clone the repo) - A virtual environment tool (venv) or similar Quick start (Windows) 1. Create and activate a virtual environment ```powershell python -m venv .venv .venv\Scripts\Activate.ps1 # PowerShell ``` 2. Install dependencies ```powershell pip install -r requirements.txt ``` 3. Run the FastAPI app (development) ```powershell # option A (run module) python app.py # option B (uvicorn) uvicorn app:app --reload --host 127.0.0.1 --port 8000 ``` 4. Open the web UI Visit http://127.0.0.1:8000 in your browser to use the TripMate frontend. Running the MCP server (example) - The repository includes `custom_weather_mcp_server.py` as an example MCP server. Run it in a separate terminal if you want to experiment with custom adapters used by the demo. ```powershell # start example MCP server (if needed) python custom_weather_mcp_server.py ``` API Endpoints - `POST /api/travel` — create or resume a travel planning thread. JSON: `{ "message": "<user prompt>", "thread_id": "optional-thread-id" }` - `POST /api/travel/approve` — approve or request revisions for a draft. JSON: `{ "thread_id": "<id>", "approved": true|false, "feedback": "optional" }` - `GET /health` — basic health check and features list Configuration & environment - Secrets and API keys are not included in the repo. Use environment variables or a `.env` file for any required keys consumed by `langgraph`, `langchain`, or other adapters. Development notes - The project keeps synchronous convenience wrappers in `backend.py` while running an async FastAPI server — `nest_asyncio` is applied in `app.py` to allow the sync helpers to call async MCP helpers. - Tests are not included; to experiment, interact with the web UI or call the API endpoints directly. Contributing - Contributions are welcome. Please open issues or pull requests for bug fixes, documentation improvements, or new adapter examples. License - This repository follows the license in the `LICENSE` file. Acknowledgements - Built as a demonstration of LangGraph + MCP patterns with supervisor and guardrail concepts. Contact - For questions or suggestions, open an issue or contact the repository owner.