csjoblom/musclesworked-mcp
by Various
MCP server for exercise-to-muscle mapping. 856 exercises, 65 muscles, 14 muscle groups with primary/secondary/stabilizer activation data.
MCP
csjoblom/musclesworked-mcp
Added 1 June 2026
Overview
An MCP server that maps 856 exercises to 65 muscles across 14 muscle groups. Provides primary, secondary, and stabilizer activation data via the Model Context Protocol.
Best for
Best for
Developers building fitness or workout applications that need detailed exercise-to-muscle relationship data
Use cases
- Query muscle activation data for specific exercises in a fitness app backend
- Generate workout plans that target distinct muscle groups using structured exercise metadata
- Analyze exercise variety and muscle coverage for training programs
How to use
Install
claude mcp add musclesworked -- npx -y musclesworked-mcp --api-key mw_live_... Tools exposed
get_muscles_workedfind_exercisesanalyze_workoutget_alternativessearch_exercisessearch_musclesMUSCLESWORKED_API_URL
Tested with
Claude Desktop, Claude Code, Cursor
Example client config
{\n "mcpServers": {\n "musclesworked": {\n "command": "npx",\n "args": ["-y", "musclesworked-mcp"],\n "env": {\n "MUSCLESWORKED_API_KEY": "mw_live_..."\n }\n }\n }\n} Notes
An MCP server that maps 856 exercises to 65 muscles across 14 muscle groups. Provides primary, secondary, and stabilizer activation data via the Model Context Protocol.
2 stars on GitHub. Last updated 2026-02-17. Licensed MIT.
Use cases
- Query muscle activation data for specific exercises in a fitness app backend
- Generate workout plans that target distinct muscle groups using structured exercise metadata
- Analyze exercise variety and muscle coverage for training programs
Pros
- Large exercise database with standardized muscle categorization
- Includes stabilizer activation details, not just primary and secondary
- Structured machine-readable format via MCP protocol
Cons
- Very low community adoption (2 GitHub stars) suggests limited use and testing
- Only provides muscle mapping, no exercise instructions, images, or equipment data
- Requires an MCP-compatible client to consume the server endpoints
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Large exercise database with standardized muscle categorization
- Includes stabilizer activation details, not just primary and secondary
- Structured machine-readable format via MCP protocol
Cons
- Very low community adoption (2 GitHub stars) suggests limited use and testing
- Only provides muscle mapping, no exercise instructions, images, or equipment data
- Requires an MCP-compatible client to consume the server endpoints
Pairs with
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