# e-worker-mcp

> e-worker-mcp — albertm88-e-worker-mcp. Use this tool when you need to streamline daily work tasks and enhance productivity through automated todo management, time tracking, and report generation. It handles tasks such as converting meeting notes into actionable items, managing todo lifecycles, and organizing files, all while providing a safety net through a human-maintained preview/apply model. Ideal for individuals and teams seeking to optimize their workflow and minimize manual administrative tasks.

Canonical page: https://skillsregistry.net/skills/albertm88-e-worker-mcp  
JSON: https://api.skillsregistry.net/v1/skills/albertm88-e-worker-mcp

## Description

A local-first MCP server that handles daily work tasks through your AI assistant: converts meeting notes into todos, manages todo lifecycle, tracks work hours, generates daily/weekly reports, organizes files via move-only operations, and diagnoses dev environments, all guarded by a human-maintained preview/apply safety model.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** productivity
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/pqgam1mzhg)
- **Repository:** <https://github.com/albertm88/e-worker-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": "albertm88-e-worker-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/albertm88-e-worker-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/albertm88-e-worker-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