# FitNotes MCP Server

> Use this tool when you need to analyze workout data from FitNotes and gain personalized insights on progress and muscle groups. It solves problems of manual data analysis and provides recommendations for improvement through a large language model (LLM) interface. The tool takes FitNotes workout data as input and outputs actionable insights and tailored suggestions for optimized training.

Canonical page: https://skillsregistry.net/skills/makkoncept-fitnotes-mcp  
JSON: https://api.skillsregistry.net/v1/skills/makkoncept-fitnotes-mcp

## Description

Enables analysis of FitNotes workout data through an LLM, providing insights on progress, muscle groups, and personalized recommendations.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/e7oqj31o9x)
- **Repository:** <https://github.com/makkoncept/fitnotes_mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "makkoncept-fitnotes-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/makkoncept-fitnotes-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/makkoncept-fitnotes-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt