musclesworked-mcp
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TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose with no overlap: analyze_workout evaluates workouts, find_exercises locates exercises by muscle, get_alternatives suggests substitutes, get_muscles_worked details muscle involvement, search_exercises finds exercises by name, and search_muscles finds muscles by name. The descriptions explicitly differentiate their functions, preventing agent confusion.
All tools follow a consistent verb_noun pattern with snake_case throughout (e.g., analyze_workout, find_exercises, get_muscles_worked). The naming is predictable and readable, using clear verbs like 'analyze', 'find', 'get', and 'search' that accurately reflect each tool's action.
With 6 tools, this server is well-scoped for its fitness/bodybuilding domain. Each tool earns its place by covering key workflows: discovering muscles and exercises, analyzing muscle involvement, finding alternatives, and evaluating workouts. The count is neither too sparse nor bloated, fitting typical agent needs efficiently.
The tool set provides strong coverage for core muscle and exercise analysis tasks, including search, retrieval, and workout evaluation. A minor gap exists in update or management operations (e.g., no tools for creating or modifying exercise/muscle data), but this is reasonable for a lookup-oriented server, and agents can work around it with the provided tools.