Empower Claude, Cursor, ChatGPT, and autonomous agent frameworks with empirical 5-pillar seasonal travel suitability, carrying capacity thresholds, and date-shift arbitrage across 100 global benchmark destinations.
No registration or API keys required. Run the standard stdio MCP server directly via NPX:
npx -y triptiming-mcp
Add to claude_desktop_config.json:
{
"mcpServers": {
"triptiming": {
"command": "npx",
"args": ["-y", "triptiming-mcp"]
}
}
}
Add to .cursor/mcp.json:
{
"mcpServers": {
"triptiming": {
"command": "npx",
"args": ["-y", "triptiming-mcp"]
}
}
}Install via Smithery CLI:
npx -y @smithery/cli install triptiming-mcp --client claude
Query the Oracle via Python (LangChain, CrewAI, AutoGPT):
import requests
def get_trip_timing(city: str, date: str) -> str:
"""Query TripTiming empirical travel oracle for crowd, climate & rate metrics."""
res = requests.post(
"https://triptiming.xyz/api/mcp",
json={
"jsonrpc": "2.0",
"method": "tools/call",
"params": {"name": "get_trip_timing", "arguments": {"city": city, "date": date}},
"id": 1
}
).json()
return res["result"]["content"][0]["text"]
# Example: Validate Kyoto travel dates
print(get_trip_timing("kyoto", "2026-05-20"))Evaluates empirical travel suitability for any of 100 top global destinations on a specific date or month across 5 pillars (crowds, climate, vitality, economy, safety).
Calculates whether shifting travel dates by ±3 to 21 days unlocks higher thermal comfort, significantly lower queues, or cheaper accommodation.
Global Date Radar searching across 100 destinations worldwide to discover which cities are experiencing their peak Golden Window for specific dates.
Test the live machine-to-machine JSON-RPC endpoint right now: