Strength Training MCP Server
A stateless MCP server exposing 8 tools for evidence-based strength training. Encodes classical powerlifting programs (5/3/1, Texas Method, Madcow, GZCLP, nSuns CAP3, Coan-Philippi, Smolov Jr), the Banister fitness-fatigue model, RPE-based autoregulation, and an adjustment policy engine.
No user data is stored on the server. All state lives in the calling agent. The server is a pure function: same inputs → same outputs.
Installation
# Install uv (one-time)
curl -LsSf https://astral.sh/uv/install.sh | sh
# Install deps + create venv
uv sync --all-extras
Running
# HTTP server
uv run python -m strength_training_mcp.server
# stdio server (Claude Desktop / Claude Code)
uv run strength-training-mcp
HTTP server starts on http://0.0.0.0:8080
- MCP JSON-RPC endpoint at
POST /mcp - Health check at
GET /health
Deployment
- ModelScope: see modelscope-deploy.md — deploy via
uvx. - Your own cloud server / VPS: see docs/selfhost.md for systemd + Caddy setup.
Quick start on any machine:
# HTTP server (for self-host / remote clients)
uvx --from strength-training-mcp strength-training-mcp-http --port 8080
# stdio server (for Claude Desktop / Claude Code local)
uvx --from strength-training-mcp strength-training-mcp
Agent Integration
See docs/agent-integration/ for setup guides:
Tools
| Tool | Purpose |
|---|---|
list_training_templates |
Browse the built-in program library |
get_template_plan |
Get a specific week's prescribed sessions |
lookup_exercise_form |
Get form cues + alternatives for an exercise |
explain_principle |
Explain a training science principle with citation |
calculate_fatigue_score |
Compute Banister CTL/ATL/TSB from training history |
suggest_session_modification |
Get adjustment recommendations based on fatigue + actual |
apply_plan_adjustment |
Apply aggregate adjustments to a week (deload, etc.) |
recommend_session_for_today |
Compose today's session with rationale |
See docs/api.md for full tool reference.
Development
uv sync --all-extras
uv run pytest tests/unit # unit tests
uv run pytest tests/integration # E2E tests
uv run pytest --cov=src/strength_training_mcp
Knowledge Sources
All templates and principles cite their original public sources. See docs/rts-principles.md for citations.
License
MIT (subject to ModelScope deployment terms).
1 maintainer
Metadata
1 maintainer
Release files for strength-training-mcp 0.1.1
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