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Travel Planning FastMCP

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AI-powered travel route planning server with budget estimation, packing suggestions, and food recommendations, using LangChain reactive agent with Tongyi Qwen a

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About

AI-powered travel route planning server with budget estimation, packing suggestions, and food recommendations, using LangChain reactive agent with Tongyi Qwen and local deterministic fallback tools.

README

Python FastMCP server for travel route planning. It uses a LangChain reactive agent with Tongyi Qwen for AI-generated itineraries and keeps local deterministic tools for budget estimation, packing suggestions, food recommendations, and offline fallback planning.

Install

python3 -m venv .venv
source .venv/bin/activate
python -m pip install -r requirements.txt

Configure Qwen/Tongyi Agent

plan_trip_route_tool calls Tongyi Qwen through DashScope. Put your API key in .env:

DASHSCOPE_API_KEY=your-real-dashscope-api-key

The server loads .env automatically before calling the LangChain agent.

Run

.venv/bin/python travel_planner_server.py

Tools

  • plan_trip_route_tool: uses a LangChain Tongyi Qwen agent to create a multi-day route with daily food recommendations, transport advice, lodging-area advice, budget reminders, and practical notes.
  • plan_trip_route_local_tool: creates a deterministic offline route when you do not want to call Qwen-Agent.
  • estimate_trip_budget_tool: estimates lodging, food, local transport, attractions, and contingency in CNY.
  • suggest_packing_list_tool: recommends essentials, seasonal items, and activity-specific items.
  • recommend_food_experiences_tool: recommends food districts, meal themes, snacks, and dietary notes.

Example MCP Client Configuration

Use the Python interpreter inside this project's virtual environment. If the MCP client uses system python3, it may fail with ModuleNotFoundError: No module named 'fastmcp'.

{
  "mcpServers": {
    "travel-planner": {
      "command": "/Users/yantao/Desktop/ai-project/TravelPlanning/.venv/bin/python",
      "args": ["/Users/yantao/Desktop/ai-project/TravelPlanning/travel_planner_server.py"]
    }
  }
}

Trae MCP Configuration

Use the same configuration in Trae:

{
  "mcpServers": {
    "travel-planner": {
      "command": "/Users/yantao/Desktop/ai-project/TravelPlanning/.venv/bin/python",
      "args": [
        "/Users/yantao/Desktop/ai-project/TravelPlanning/travel_planner_server.py"
      ]
    }
  }
}

After changing the configuration, reload the MCP server or restart Trae.

Troubleshooting

If you see:

ModuleNotFoundError: No module named 'fastmcp'

the MCP client is using the wrong Python interpreter. Install dependencies first:

python3 -m venv .venv
.venv/bin/python -m pip install -r requirements.txt

Then make sure the MCP command points to:

/Users/yantao/Desktop/ai-project/TravelPlanning/.venv/bin/python

Development

env PYTEST_DISABLE_PLUGIN_AUTOLOAD=1 python3 -m pytest -q
python3 -m compileall travel_planner.py qwen_travel_agent.py travel_planner_server.py

from github.com/yantaotaotao/TravelPlanning

Installing Travel Planning FastMCP

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/yantaotaotao/TravelPlanning

FAQ

Is Travel Planning FastMCP MCP free?

Yes, Travel Planning FastMCP MCP is free — one-click install via Unyly at no cost.

Does Travel Planning FastMCP need an API key?

No, Travel Planning FastMCP runs without API keys or environment variables.

Is Travel Planning FastMCP hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Travel Planning FastMCP in Claude Desktop, Claude Code or Cursor?

Open Travel Planning FastMCP on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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