Testing OpenClaw for Multi-Country Trip Planning with MoLOS Integration
OpenClaw and MoLOS Stack for Automated Travel Planning
A developer tested OpenClaw's capabilities beyond standard ChatGPT responses by using it with MoLOS to plan a multi-city China-Japan trip with minimal manual intervention.
Technical Setup and Process
The test used a self-hosted stack with:
- MoLOS as a structured productivity memory layer for managing tasks and notes
- OpenClaw as an AI agent operator for actions
The process involved:
- Feeding the system with trip data: dates, interests, and budget
- Letting OpenClaw create planning tasks automatically
- Generating day-by-day itineraries
- Suggesting flights and hotels
- Assigning places to visit
- MoLOS logging everything into tasks/projects
What Worked
- Initial itinerary was structured and detected scheduling overlaps
- Automatic time adjustments for conflicts
- Centralized data storage in MoLOS prevented data loss across apps
- Automatic task creation (e.g., "Book Beijing-Shanghai flight" and "Buy JR Rail Pass")
- Approval workflow: user reviewed city options and bookings, then wrote decisions into tasks
- MoLOS automatically communicated with OpenClaw to continue the workflow
- Resulted in an editable plan with 50+ completed tasks and complete trip documentation
Limitations Identified
- Errors in transport times (sometimes off)
- Some attractions were invalid
- Manual validation still required for visas and access requirements
- Not a 100% autonomous system yet
The developer described the experience as less about using isolated tools and more about supervising a system that thinks for them, with OpenClaw and MoLOS currently serving as their day-to-day productivity driver.
📖 Read the full source: r/openclaw
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