Pelaris

by theDonk

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GitHub

About

Connect Pelaris to any MCP-compatible AI assistant for personalised fitness coaching. Plan training programs, log workouts, track benchmarks, manage goals, and get data-driven coaching insights.

Explore

- 21 tools for reading and writing training data
- Read tools: training overview, programs, sessions, benchmarks, body analysis, coaching insights
- Write tools: log workouts, create sessions, manage goals, record injuries, generate plans
- Supports strength, running, swimming, cycling, triathlon, CrossFit, and general fitness
- Implements 28 science‑based training methodologies
- OAuth 2.0 with PKCE and optional Dynamic Client Registration
- Pseudonymous user IDs and PII scrubbing on responses

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Pelaris

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

From the repository

OAuth 2.0 with PKCE. The server supports:
- Pre-registered clients for ChatGPT and Claude
- Dynamic Client Registration for all other MCP clients

`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

`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

`create_planned_session`

Create a planned workout with exercises and targets

`log_workout`

Log a completed workout or mark a planned session as done

`swap_exercise`

Get alternative exercise suggestions

`modify_training_session`

Adjust session volume, intensity, or schedule

`record_injury`

Record an injury with body part, severity, and notes

`update_profile`

Update equipment, availability, and preferences

`send_feedback`

Submit coaching quality feedback

`generate_weekly_plan`

Generate a new training plan

`record_benchmark`

Record a benchmark value with history tracking

`daily_check_in`

Log daily readiness, soreness, and sleep quality

`manage_goals`

Create, update, complete, or list training goals

`manage_program`

View, archive, or manage training programs

| 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 |
| 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 |

| Tool | Description |
|------|-------------|
| create_planned_session | Create a planned workout with exercises and targets |
| log_workout | Log a completed workout or mark a planned session as done |
| swap_exercise | Get alternative exercise suggestions |
| modify_training_session | Adjust session volume, intensity, or schedule |
| record_injury | Record an injury with body part, severity, and notes |
| update_profile | Update equipment, availability, and preferences |
| send_feedback | Submit coaching quality feedback |
| generate_weekly_plan | Generate a new training plan |
| record_benchmark | Record a benchmark value with history tracking |
| daily_check_in | Log daily readiness, soreness, and sleep quality |
| manage_goals | Create, update, complete, or list training goals |
| manage_program | View, archive, or manage training programs |

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "pelaris": {
            "pelaris": {
                "url": "https://api.pelaris.io/mcp"
            }
        }
    }
}

McpServers

{
    "pelaris": {
        "url": "https://api.pelaris.io/mcp"
    }
}

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 (21)

Read Tools (9)

| 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 | | 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 |

Write Tools (12)

| Tool | Description | |------|-------------| | create_planned_session | Create a planned workout with exercises and targets | | log_workout | Log a completed workout or mark a planned session as done | | swap_exercise | Get alternative exercise suggestions | | modify_training_session | Adjust session volume, intensity, or schedule | | record_injury | Record an injury with body part, severity, and notes | | update_profile | Update equipment, availability, and preferences | | send_feedback | Submit coaching quality feedback | | generate_weekly_plan | Generate a new training plan | | record_benchmark | Record a benchmark value with history tracking | | daily_check_in | Log daily readiness, soreness, and sleep quality | | manage_goals | Create, update, complete, or list training goals | | manage_program | View, archive, or manage training programs |

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

Built by

Bradley Hunt · About Pelaris

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About

Explore

Setting up with Highlight

From the repository

get_training_overview

get_active_program

get_session_details

get_benchmarks

get_body_analysis

search_training_resources

get_coach_insight

get_onboarding_status

get_weekly_debrief

create_planned_session

log_workout

swap_exercise

modify_training_session

record_injury

update_profile

send_feedback

generate_weekly_plan

record_benchmark

daily_check_in

manage_goals

manage_program

Claude Desktop / Cursor

McpServers

Connect

ChatGPT

Claude

Any MCP Client

Tools (21)

Read Tools (9)

Write Tools (12)

Authentication

Sports Supported

Privacy

Built by

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`get_training_overview`

`get_active_program`

`get_session_details`

`get_benchmarks`

`get_body_analysis`

`search_training_resources`

`get_coach_insight`

`get_onboarding_status`

`get_weekly_debrief`

`create_planned_session`

`log_workout`

`swap_exercise`

`modify_training_session`

`record_injury`

`update_profile`

`send_feedback`

`generate_weekly_plan`

`record_benchmark`

`daily_check_in`

`manage_goals`

`manage_program`