Pelaris
将Pelaris连接到任何兼容MCP的AI助手，获取个性化健身指导。制定训练计划、记录锻炼、追踪基准、管理目标，并获得数据驱动的教练洞察。
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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