Travel Planning FastMCP
FreeNot checkedAI-powered travel route planning server with budget estimation, packing suggestions, and food recommendations, using LangChain reactive agent with Tongyi Qwen a
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
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/TravelPlanningFAQ
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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