How to Build Exercise Libraries at Scale with OpenClaw
Build exercise content libraries at scale with OpenClaw and ToolRouter.
Tool
OpenClaw builds comprehensive exercise content libraries in a single batch operation, pulling the complete exercise database for use in fitness platforms, personal training software, and content systems that need a rich, categorised exercise reference without assembling it manually.
Connect ToolRouter to OpenClaw
1Install the CLI
npm install -g toolrouter-mcp2Call tools directly from OpenClaw
toolrouter-mcp call web-search search --query "AI tools"
toolrouter-mcp toolsSteps
Once connected (see setup above), use the Workout Planner tool:
- Run: "Browse all exercises across all categories using workout-planner"
- OpenClaw returns the complete exercise library
- Load into your fitness platform database
- Refresh quarterly to incorporate any newly added exercises
Example Prompt
Try this with OpenClaw using the Workout Planner tool
Browse all exercises using workout-planner and return as a complete JSON library categorised by body part, with name, target muscle, secondary muscles, equipment, and difficulty for each.
Tips
- Pull the full library once and build a local search index for fast in-app filtering
- Build category taxonomies from the body part and target muscle fields for browse navigation
- Add exercises to a favourites or programme system using the exercise ID as a stable reference key