| # Travel Documentation MCP Server | |
| > An AI-powered travel documentation assistant built with Gradio's MCP server capabilities and smolagents for the Hugging Face MCP Hackathon 2025. | |
| ## What This Project Does | |
| This project creates an intelligent travel documentation agent that helps travelers understand what documents they need for international trips. It consists of: | |
| 1. **MCP Server** (`travel_mcp_server.py`) - A Gradio interface that exposes travel documentation analysis as an MCP tool, mocking data is used for demonstration | |
| 2. **MCP Client** (`travel_mcp_client.py`) - An AI agent that uses smolagents to interact with the MCP server and provide conversational assistance | |
| ## Technical Implementation | |
| - **Gradio MCP Server**: Uses Gradio's built-in MCP server functionality | |
| - **smolagents Integration**: AI agent framework for tool execution and conversation | |
| - **Local LLM Support**: Uses Ollama for local AI inference | |
| ## Installation & Setup | |
| ### Prerequisites | |
| - Python 3.8+ | |
| - Ollama (for local LLM) | |
| ### 1. Install Dependencies | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| ### 2. Set up Ollama (for the AI agent) | |
| ```bash | |
| # Install Ollama from https://ollama.ai | |
| # Pull the required model | |
| ollama pull gemma3:4b | |
| ``` | |
| ### 3. Start the MCP Server | |
| ```bash | |
| python travel_mcp_server.py | |
| ``` | |
| The server will start at `http://127.0.0.1:7861` with MCP endpoint at `http://127.0.0.1:7861/gradio_api/mcp/sse` | |
| ### 4. Start the AI Agent Client | |
| ```bash | |
| python travel_mcp_client.py | |
| ``` | |
| ## Usage | |
| ### Direct Web Interface | |
| Visit `http://127.0.0.1:7861` to use the travel documentation tool directly: | |
| **Input Parameters:** | |
| - **Your Citizenship Country**: e.g., "Canada", "China", "India" | |
| - **Destination Country**: e.g., "Japan", "USA", "Germany" | |
| - **Trip Duration**: Number of days (1-365) | |
| - **Trip Purpose**: tourism, business, study, transit, work, family visit | |
| **Example Output:** | |
| ```json | |
| { | |
| "trip_info": { | |
| "from_country": "Canada", | |
| "to_country": "Japan", | |
| "duration_days": 30, | |
| "purpose": "Tourism" | |
| }, | |
| "visa_requirements": { | |
| "visa_required": false, | |
| "max_stay": "90 days" | |
| }, | |
| "required_documents": [ | |
| { | |
| "document_type": "Passport", | |
| "required": true, | |
| "description": "Valid passport with at least 6 months validity remaining" | |
| } | |
| ], | |
| "summary": { | |
| "required_count": 5, | |
| "optional_count": 1, | |
| "visa_needed": false | |
| } | |
| } | |
| ``` | |
| ### AI Agent Chat Interface | |
| Use the conversational agent for natural language queries: | |
| **Example Conversations:** | |
| ``` | |
| User: "I'm a Canadian citizen planning to visit Japan for 2 weeks for tourism" | |
| Agent: "..." | |
| User: "What documents do I need for business travel from China to USA?" | |
| Agent: "..." | |
| ``` | |