pelaris-mcp-server
Pelaris
Documentation
Pelaris MCP Server
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**
Connect
MCP Server URL: `https://api.pelaris.io/mcp`
ChatGPT
Settings → Apps → Add → enter the MCP Server URL above
Claude
Settings → Connectors → Add Custom → enter the MCP Server URL above → Advanced Settings → Client ID: `pelaris-claude`
Any MCP Client
Connect to `https://api.pelaris.io/mcp` — supports OAuth 2.0 with PKCE and Dynamic Client Registration.
Tools (31)
Read Tools (13)
| Tool | Description |
|---|---|
| `get_training_overview` | View your training context, active programs, and recent sessions |
| `get_active_program` | View current program with phase, weekly structure, and session details |
| `get_session_details` | View a specific session's exercises, sets, targets, and feedback |
| `resolve_exercise_ids` | Resolve exercise names to canonical exercise IDs before planning or logging |
| `get_benchmarks` | View benchmark values, progress history, and trends |
| `get_body_analysis` | View body composition data and measurement trends |
| `search_training_resources` | Search curated training articles and resources |
| `get_coach_insight` | Get data-driven coaching insights based on your training |
| `get_onboarding_status` | Check profile setup completion status |
| `get_weekly_debrief` | View weekly training summary and coaching focus |
| `get_generation_status` | Check the status of an in-progress program-generation job |
| `get_program_status` | Check the status and progress of your training programs |
| `list_goals` | List your training goals with completion status and linked benchmarks |
Write Tools (18)
| Tool | Description |
|---|---|
| `complete_intake` | Complete onboarding intake and persist your training profile |
| `generate_program` | Generate and enrol a full training program from your profile |
| `create_planned_session` | Create a planned workout with exercises and targets |
| `log_workout` | Log a completed workout or mark a planned session as done |
| `log_completed_session` | Log a full completed session with exercises, sets, and feedback |
| `swap_exercise` | Get alternative exercise suggestions |
| `modify_training_session` | Adjust session volume, intensity, or schedule |
| `update_session` | Update the details of an existing planned session |
| `delete_session` | Delete a single planned session |
| `delete_sessions` | Delete multiple planned sessions |
| `record_injury` | Record an injury with body part, severity, and notes |
| `update_profile` | Update equipment, availability, and preferences |
| `send_feedback` | Submit coaching quality feedback |
| `record_benchmark` | Record a benchmark value with history tracking |
| `daily_check_in` | Log daily readiness, soreness, and sleep quality |
| `manage_goals` | Create, update, or complete training goals |
| `manage_program` | View, archive, or manage training programs |
| `generate_weekly_plan` | Legacy short-plan generator (superseded by `generate_program`) |
Example prompts
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.)
Authentication
OAuth 2.0 with PKCE. The server supports:
- Pre-registered clients for ChatGPT and Claude
- Dynamic Client Registration for all other MCP clients
Sports Supported
Strength · Running · Swimming · Cycling · Triathlon · CrossFit · General Fitness
Pelaris implements 28 science-based training methodologies. Learn more about our methodology.
Privacy
- 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
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Frequently asked questions
What is pelaris-mcp-server?
pelaris-mcp-server is Pelaris
How do I install pelaris-mcp-server?
Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.
Is pelaris-mcp-server open source?
Yes — it is hosted on GitHub at https://github.com/theDonk/pelaris-mcp-server.
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