Pierre Fitness Platform

Pierre Fitness Platform connects AI assistants to fitness data from Strava, Garmin, Fitbit, WHOOP, COROS, and Terra (150+ wearables). Implements Model Context Protocol (MCP), A2A protocol, OAuth 2.0, and REST APIs for Claude, ChatGPT, and other AI assistants.

Intelligence System

Sports science-based fitness analysis including training load management, race predictions, sleep and recovery scoring, nutrition planning, and pattern detection.

See Intelligence Methodology and Nutrition Methodology for details.

Features

MCP Protocol: JSON-RPC 2.0 for AI assistant integration
A2A Protocol: Agent-to-agent communication
OAuth 2.0 Server: RFC 7591 dynamic client registration
47 MCP Tools: Activities, goals, analysis, sleep, recovery, nutrition, recipes, configuration
TypeScript SDK: pierre-mcp-client npm package
Pluggable Providers: Compile-time provider selection
TOON Format: Token-Oriented Object Notation output for ~40% LLM token reduction (spec)

Provider Support

Provider	Feature Flag	Capabilities
Strava	`provider-strava`	Activities, Stats, Routes
Garmin	`provider-garmin`	Activities, Sleep, Health
WHOOP	`provider-whoop`	Sleep, Recovery, Strain
Fitbit	`provider-fitbit`	Activities, Sleep, Health
COROS	`provider-coros`	Activities, Sleep, Recovery
Terra	`provider-terra`	150+ wearables, Activities, Sleep, Health
Synthetic	`provider-synthetic`	Development/Testing

Build with specific providers:

cargo build --release                                                    # all providers
cargo build --release --no-default-features --features "sqlite,provider-strava"  # strava only

See Pluggable Provider Architecture.

Modular Architecture

Pierre uses compile-time feature flags for modular deployments. Build only what you need.

Server Profiles

Pre-configured bundles for common deployment scenarios:

Profile	Description	Binary Size
`server-full`	All protocols, transports, clients (default)	~50MB
`server-mcp-stdio`	MCP protocol + stdio transport (desktop clients)	~35MB
`server-mcp-bridge`	MCP + A2A protocols, web transports	~40MB
`server-mobile-backend`	REST + MCP, mobile client routes	~42MB
`server-saas-full`	REST + MCP, web + admin clients	~45MB

# Build for desktop MCP clients (minimal)
cargo build --release --no-default-features --features "sqlite,server-mcp-stdio"

# Build for SaaS deployment
cargo build --release --no-default-features --features "postgresql,server-saas-full"

Feature Categories

Category	Features	Description
Protocols	`protocol-rest`, `protocol-mcp`, `protocol-a2a`	API protocols
Transports	`transport-http`, `transport-websocket`, `transport-sse`, `transport-stdio`	Communication layers
Clients	`client-web`, `client-admin`, `client-mobile`	Route groups
Tools	`tools-fitness-core`, `tools-wellness`, `tools-all`	MCP tool categories

See Build Configuration for detailed feature documentation.

What You Can Ask

"Calculate my daily nutrition needs for marathon training"
"Analyze my training load - do I need a recovery day?"
"Compare my three longest runs this month"
"Analyze this meal: 150g chicken, 200g rice, 100g broccoli"
"What's my predicted marathon time based on recent runs?"

See Tools Reference for the 47 available MCP tools.

Quick Start

git clone https://github.com/Async-IO/pierre_mcp_server.git
cd pierre_mcp_server
cp .envrc.example .envrc  # edit with your settings
direnv allow              # or: source .envrc
./bin/setup-and-start.sh  # complete setup: fresh DB, admin user, server start

Server starts on http://localhost:8081. See Getting Started for detailed setup.

MCP Client Configuration

Add to Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "pierre-fitness": {
      "command": "npx",
      "args": ["-y", "pierre-mcp-client@next", "--server", "http://localhost:8081"]
    }
  }
}

The SDK handles OAuth 2.0 authentication automatically. See SDK Documentation.

Available MCP Tools

47 tools organized in 8 categories:

Category	Tools	Description
Core Fitness	6	Activities, athlete profile, provider connections
Goals	4	Goal setting, suggestions, feasibility, progress
Analysis	10	Metrics, trends, patterns, predictions, recommendations
Sleep & Recovery	5	Sleep quality, recovery score, rest recommendations
Nutrition	5	BMR/TDEE, macros, USDA food search, meal analysis
Recipes	7	Training-aware meal planning and recipe storage
Configuration	6	User settings, training zones, profiles
Fitness Config	4	Fitness parameters, thresholds

Full tool reference: docs/tools-reference.md

Server Management

./bin/setup-and-start.sh  # complete setup: fresh DB, admin user, server start
./bin/start-server.sh     # start backend only (loads .envrc)
./bin/stop-server.sh      # stop backend
./bin/start-frontend.sh   # start dashboard (http://localhost:5173)

Options for setup-and-start.sh:

--skip-fresh-start - preserve existing database
--run-tests - run workflow tests after startup
--admin-email EMAIL - custom admin email
--admin-password PWD - custom admin password

User Portal Dashboard

Web-based dashboard for users and administrators at http://localhost:5173.

Features

Role-Based Access: super_admin, admin, user roles with permission hierarchy
User Registration: Self-registration with admin approval workflow
API Key Management: Create, view, deactivate API keys
MCP Tokens: Generate tokens for Claude Desktop and AI assistants
Usage Analytics: Request patterns, tool usage charts
Super Admin Impersonation: View dashboard as any user for support

User Roles

Role	Capabilities
User	Own API keys, MCP tokens, analytics
Admin	+ User approval, all users analytics
Super Admin	+ Impersonation, admin tokens, system config

First Admin Setup

cargo run --bin admin-setup -- create-admin-user \
  --email [email protected] \
  --password SecurePassword123 \
  --super-admin

See Frontend Documentation for detailed dashboard documentation.

Mobile App

React Native mobile app for iOS and Android with conversational AI interface.

Features

AI Chat Interface: Conversational UI with markdown rendering and real-time streaming
Fitness Provider Integration: Connect to Strava, Garmin, Fitbit, WHOOP, COROS via OAuth
Activity Tracking: View and analyze your fitness activities
Training Insights: Get AI-powered training recommendations

Quick Start

cd frontend-mobile
bun install
bun start   # Start Expo development server
bun run ios # Run on iOS Simulator

See Mobile App README and Mobile Development Guide.

AI Coaches

Pierre includes an AI coaching system with 9 default coaching personas and support for user-created personalized coaches.

Default Coaches

The system includes 9 AI coaching personas across 5 categories:

Category	Icon	Coaches
Training	🏃	Endurance Coach, Speed Coach
Nutrition	🥗	Sports Nutritionist, Hydration Specialist
Recovery	😴	Recovery Specialist, Sleep Coach
Recipes	👨‍🍳	Performance Chef, Meal Prep Expert
Analysis	📊	Data Analyst

Default coaches are seeded automatically by ./bin/setup-and-start.sh and are visible to all users.

Personalized Coaches

Users can create their own AI coaches with custom:

Name and personality
System prompts and behavior
Category assignment
Avatar customization

User-created coaches appear in a "Personalized" section above system coaches and are private to each user.

Coach Seeder

To seed or refresh the default coaches:

cargo run --bin seed-coaches

This creates the 9 default AI coaching personas if they don't already exist.

Documentation

Reference

Getting Started - installation, configuration, first run
Architecture - system design, components, request flow
Protocols - MCP, OAuth2, A2A, REST
Authentication - JWT, API keys, OAuth2 flows
Configuration - environment variables, algorithms

Development

Development Guide - workflow, dashboard, testing
Scripts Reference - 30+ development scripts
CI/CD - GitHub Actions, pipelines
Release Guide - releasing server and SDK to npm
Contributing - code standards, PR workflow

Components

SDK - TypeScript client for MCP integration
Frontend - React dashboard
Mobile - React Native mobile app
Mobile Development - mobile dev setup guide

Methodology

Intelligence - sports science formulas
Nutrition - dietary calculations

Testing

cargo test                        # all tests
./scripts/lint-and-test.sh        # full CI suite
./scripts/smoke-test.sh           # quick validation (~3 min)

See Testing Documentation.

Development Workflow

Before Committing

# 1. Format code
cargo fmt

# 2. Architectural validation
./scripts/architectural-validation.sh

# 3. Clippy (strict mode)
cargo clippy --all-targets -- -D warnings -D clippy::all -D clippy::pedantic -D clippy::nursery

# 4. Run relevant tests
cargo test <test_pattern>

Before Pushing

# 1. Enable git hooks (once per clone)
git config core.hooksPath .githooks

# 2. Run validation (creates marker valid for 15 min)
./scripts/pre-push-validate.sh

# 3. Push (hook checks for valid marker)
git push

The pre-push hook blocks pushes without a valid marker. This decouples test execution from the push to avoid SSH timeout issues.

Contributing

See Contributing Guide.

License

Dual-licensed under Apache 2.0 or MIT.

Name		Name	Last commit message	Last commit date
Latest commit History 1,200 Commits
.claude		.claude
.githooks		.githooks
.github		.github
benches		benches
bin		bin
coaches		coaches
docker		docker
docs		docs
examples		examples
frontend-mobile		frontend-mobile
frontend		frontend
load-tests		load-tests
migrations		migrations
scripts		scripts
sdk		sdk
src		src
templates		templates
test_data		test_data
tests		tests
website		website
.dockerignore		.dockerignore
.env.postgres.example		.env.postgres.example
.envrc.example		.envrc.example
.gitignore		.gitignore
.mcp.json		.mcp.json
.nvmrc		.nvmrc
AGENTS.md		AGENTS.md
CHANGELOG.md		CHANGELOG.md
CONTRIBUTING.md		CONTRIBUTING.md
Cargo.lock		Cargo.lock
Cargo.toml		Cargo.toml
LICENSE-APACHE		LICENSE-APACHE
LICENSE-MIT		LICENSE-MIT
LICENSE.md		LICENSE.md
README.md		README.md
SECURITY.md		SECURITY.md
build.rs		build.rs
clippy.toml		clippy.toml
deny.toml		deny.toml
docker-compose.yml		docker-compose.yml
llms.txt		llms.txt
package.json		package.json
rust-toolchain		rust-toolchain
token_output.txt		token_output.txt

Uh oh!

License

Licenses found

Async-IO/pierre_mcp_server

Folders and files

Latest commit

History

Repository files navigation

Pierre Fitness Platform

Intelligence System

Features

Provider Support

Modular Architecture

Server Profiles

Feature Categories

What You Can Ask

Quick Start

MCP Client Configuration

Available MCP Tools

Server Management

User Portal Dashboard

Features

User Roles

First Admin Setup

Mobile App

Features

Quick Start

AI Coaches

Default Coaches

Personalized Coaches

Coach Seeder

Documentation

Reference

Development

Components

Methodology

Testing

Development Workflow

Before Committing

Before Pushing

Contributing

License

About

Topics

Resources

License

Licenses found

Contributing

Security policy

Uh oh!

Stars

Watchers

Forks

Releases 2

Sponsor this project

Uh oh!

Uh oh!

Contributors 4

Uh oh!

Languages