AI fitness coaching through any MCP-compatible AI assistant. Plan training, log workouts, track benchmarks, manage goals, and get coaching insights — all through natural conversation.
Website · Integrations Guide · How It Works · Methodology
MCP Server URL: https://api.pelaris.io/mcp
Settings → Apps → Add → enter the MCP Server URL above
Settings → Connectors → Add Custom → enter the MCP Server URL above → Advanced Settings → Client ID: pelaris-claude
Connect to https://api.pelaris.io/mcp — supports OAuth 2.0 with PKCE and Dynamic Client Registration.
Related MCP server: TrackLab MCP Ultimate Edition
Tool | Description |
| View your training context, active programs, and recent sessions |
| View current program with phase, weekly structure, and session details |
| View a specific session's exercises, sets, targets, and feedback |
| Resolve exercise names to canonical exercise IDs before planning or logging |
| View benchmark values, progress history, and trends |
| View body composition data and measurement trends |
| Search curated training articles and resources |
| Get data-driven coaching insights based on your training |
| Check profile setup completion status |
| View weekly training summary and coaching focus |
| Check the status of an in-progress program-generation job |
| Check the status and progress of your training programs |
| List your training goals with completion status and linked benchmarks |
Tool | Description |
| Complete onboarding intake and persist your training profile |
| Generate and enrol a full training program from your profile |
| Create a planned workout with exercises and targets |
| Log a completed workout or mark a planned session as done |
| Log a full completed session with exercises, sets, and feedback |
| Get alternative exercise suggestions |
| Adjust session volume, intensity, or schedule |
| Update the details of an existing planned session |
| Delete a single planned session |
| Delete multiple planned sessions |
| Record an injury with body part, severity, and notes |
| Update equipment, availability, and preferences |
| Submit coaching quality feedback |
| Record a benchmark value with history tracking |
| Log daily readiness, soreness, and sleep quality |
| Create, update, or complete training goals |
| View, archive, or manage training programs |
| Legacy short-plan generator (superseded by |
Once connected, talk to your AI assistant naturally. It maps your intent to the tools above:
"What does my training look like today?" → get_training_overview / get_active_program
"Log my 5k run, felt easy, RPE 4." → log_workout
"Create an upper body session for tomorrow." → create_planned_session
"How are my benchmarks trending?" → get_benchmarks
"Swap the barbell bench for a dumbbell variation." → swap_exercise
"My right shoulder's been sore." → record_injury
"Build me a 4-week running plan." → generate_program
(Illustrative prompts only; no personal data is shown. Responses are grounded in your own training data and PII-scrubbed.)
OAuth 2.0 with PKCE. The server supports:
Pre-registered clients for ChatGPT and Claude
Dynamic Client Registration for all other MCP clients
Strength · Running · Swimming · Cycling · Triathlon · CrossFit · General Fitness
Pelaris implements 28 science-based training methodologies. Learn more about our methodology.
Pseudonymous user IDs (Firebase UIDs are never exposed)
PII scrubbing on all responses
Granular OAuth scopes
Users can disconnect anytime
Privacy Policy · Terms of Service
This server cannot be deployed
Pace is a remote MCP server that exposes wearable and fitness data to Claude via the Model Context Protocol. It connects to Garmin, Oura, Whoop, Polar, Fitbit and 20+ devices and provides 15 tools for querying sleep, activity, recovery, and training data. Hosted on Google Cloud Run, OAuth 2.1 authentication, Streamable HTTP transport. Instructions: First you need to create an account at: https://pacetraining.co and connect your wearables. After that you can connect the remote Server via Custom Connector in Claude and OAuth 2.1 Flow startet.
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