# mcp-wger

> mcp-wger — pipeworx-io-mcp-wger. Use this tool when you need to manage and serve workout and exercise data from wger, providing a centralized server for accessing and updating fitness information, with integration capabilities via git for version control and collaboration. It solves problems related to data consistency and accessibility in fitness tracking and planning. Ideal for use cases involving personalized workout routines, exercise databases, and health monitoring applications.

Canonical page: https://skillsregistry.net/skills/pipeworx-io-mcp-wger  
JSON: https://api.skillsregistry.net/v1/skills/pipeworx-io-mcp-wger

## Description

MCP server for wger workout and exercise data

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/pipeworx-io/mcp-wger)

## 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": "pipeworx-io-mcp-wger"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/pipeworx-io-mcp-wger` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/pipeworx-io-mcp-wger/pull`

---
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