What is MCP and how does this server use it?
The Model Context Protocol (MCP) enables AI assistants to understand and interact with the API directly. This server uses the fastapi_mcp library to expose API endpoints via an SSE endpoint at `/mcp`.
@aryanranderiya
基本信息
FastAPI-based travel itinerary system with MCP integration for AI-powered discovery, filtering, and creation of travel plans via natural language.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"itinerary-mcp-server": {
"command": "uv",
"args": [
"venv"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
A FastAPI-based backend for managing travel itineraries, implementing the Model Context Protocol (MCP) for AI assistant integration. It provides RESTful endpoints to create and view trip itineraries, with pre-populated seed data for Phuket and Krabi regions. Designed for developers and AI tool users who need a structured travel planning backend.
Install Python 3.8+, clone the repository, create a virtual environment with uv venv and install dependencies with uv sync. Run the server in development mode using fastapi dev or production mode with fastapi start. The MCP integration is built-in – connect any MCP-compatible client (e.g., GitHub Copilot, Claude Desktop) to the SSE endpoint at http://localhost:8000/mcp. No additional configuration is needed.
/mcpThe Model Context Protocol (MCP) enables AI assistants to understand and interact with the API directly. This server uses the fastapi_mcp library to expose API endpoints via an SSE endpoint at `/mcp`.
Python 3.8 or higher, and the uv package manager for Python.
For development with auto-reload: `fastapi dev`. For production: `fastapi start`. The API is then available at `http://localhost:8000`.
Any MCP-compatible client, including GitHub Copilot, Claude Desktop, and other MCP-compatible assistants.
Yes, the database is pre-populated with realistic seed data for the Phuket and Krabi regions, including sample itineraries of 2–8 nights.
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