Skip to main content
Glama
daiduo2

strength-training-mcp

by daiduo2

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

Related MCP server: MCP Logger

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

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).

Install Server
A
license - permissive license
A
quality
B
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/daiduo2/strength-training-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server