Dida-RollingGo-Hotel-MCP-Global
Eliminates custom hotel booking integrations and data sourcing overhead.
Official DIDA Hotel Booking MCP Server. 14-year travel tech data stack, 2M+ hotels at wholesale rates, 40+ LLM compatible. Free unlimited calls for businesses & individual devs. Filter by location, date, star grade, guests & tags; pull real-time room types, pricing & cancellation rules.
- Generate hotel availability reports filtered by location, dates, and star ratings for client proposals.
- Automate bulk pricing lookups across multiple hotel chains to compare wholesale rates instantly.
- Find cancellation policy details for specific properties to help clients understand booking terms.
Eliminates custom hotel booking integrations and data sourcing overhead. Direct access to 2M+ properties at wholesale pricing reduces vendor lock-in and enables real-time rate comparison at scale.
Travel platforms, expense management systems, and enterprise travel consultants building booking workflows or rate intelligence features.
https://github.com/DIDA-AI/Dida-RollingGo-Hotel-MCP-Global
By DIDA-AI
How to Get It
claude mcp add Dida-RollingGo-Hotel-MCP-Global -- npx -y Dida-RollingGo-Hotel-MCP-Global
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
Once it’s connected, paste this into Claude:
Help me generate hotel availability reports filtered by location, dates, and star ratings for client proposals
Trust Signals Auto-scanned
Data & Access
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 81 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 81 GitHub stars; contributors unknown; last commit 0d ago; license MIT.