Connects to the Trip.com / Ctrip Group travel supply chain to route and optimize itineraries — covering flights, high-speed rail, hotels, visas, attractions, and ground transfers — with crowd-density-aware destination routing, TSP-based schedule optimization under fatigue and opening-hour constraints, probabilistic airfare price forecasting, and corporate travel compliance/expense verification.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@genpark-ctrip-destination-crowd-density-router-skill Route me through Shanghai Disneyland now with the shortest queue waits"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
In the era of vertical foundation models, Ctrip / Trip.com Group pioneered the travel industry's vertical intelligence platform (Ctrip Quest / 携程问道) and multi-agent service ecosystem (TripGenie & Corporate Travel Agents). Travel planning inherently presents multi-dimensional combinatorial NP-hard challenges: volatile flight yield curves, fluctuating hotel price parities, international cross-border visa jurisdictions, and peak attraction crowd bottlenecks.
This skill library distills the core mathematical logic and agent orchestration models powering the next-generation GenPark Ctrip AI Travel Agent OS:
Combinatorial Itinerary Optimization: Dynamic TSP graph solver with fatigue and opening hour constraints.
Yield Management & Price Forecasting: Probabilistic expected-value airline pricing hazard models.
Cross-Surface Compliance & Verification: Cryptographic policy checks and zero-friction corporate expense auditing.
Enterprise Protocol Parity: Full native Model Context Protocol (MCP) compliance for agentic runtime integration.
Related MCP server: mendicant-mcp-server
flowchart TD
subgraph UserIntent["Traveler / Corporate Traveler Intent"]
Prompt[Natural Language Travel Request] --> Parser[Multi-Modal Semantic Parser]
end
subgraph AgentCore["GenPark Ctrip Agent Core"]
Parser --> CoreEngine["GenParkCtripDestinationCrowdDensityRouter"]
CoreEngine --> DomainMath[Mathematical Modeling & Constraint Satisfaction]
DomainMath --> OutputPayload[Optimized Schedule / Decision Payload / MCP Response]
end
subgraph SupplyChain["Ctrip Global Supply Chain & Inventory"]
OutputPayload --> GlobalGDS[Flights, High-Speed Rail & Hotels]
OutputPayload --> LocalServices[Visas, Attractions & Ground Transfers]
endCapability | Specification |
Runtime Environment | Python 3.9+ (Standard Library Only) |
External Dependencies | None (0 packages) |
Protocol Compatibility | Anthropic Model Context Protocol (MCP) STDIO JSON-RPC 2.0 |
Architecture Paradigm | Pure Functional & Mathematical Modeling |
Deployment Mode | Headless Agent Skill, CLI Client, or MCP Server |
python example_usage.pyRun the native STDIO MCP server for Claude Desktop, Cursor, or Antigravity integration:
python mcp_server.pyAdd to your claude_desktop_config.json or agent runner config:
{
"mcpServers": {
"genpark-ctrip-destination-crowd-density-router-skill": {
"command": "python",
"args": ["path/to/genpark-ctrip-destination-crowd-density-router-skill/mcp_server.py"]
}
}
}Engineered with zero external dependencies using pure Python standard library code. This ensures instantaneous cold starts, sub-millisecond execution overhead, and zero package version conflicts across diverse agent runtime environments.
Run python mcp_server.py --test to verify MCP protocol discovery and tool schema negotiation.
This project is licensed under the MIT License - see the LICENSE file for details.
This server cannot be deployed
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