# ActivityWatch

> Use this tool when you need to analyze personal activity data and enhance productivity analysis for AI assistants. It connects to ActivityWatch, allowing interaction with time tracking data through listing buckets, executing AQL queries, and retrieving raw events. This enables LLMs to solve problems related to time management and productivity tracking, accepting inputs like AQL queries and bucket names, and outputting relevant time tracking data.

Canonical page: https://skillsregistry.net/skills/8bitgentleman-activitywatch  
JSON: https://api.skillsregistry.net/v1/skills/8bitgentleman-activitywatch

## Description

This MCP server connects to ActivityWatch, enabling LLMs like Claude to interact with time tracking data. It provides tools for listing buckets, executing AQL queries, and retrieving raw events from any bucket. Developed by Matt Vogel, it's designed to enhance productivity analysis and time management capabilities for AI assistants working with personal activity data.

## Trust

- **Trust score (0–1):** 0.63
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/8bitgentleman-activitywatch)
- **Repository:** <https://github.com/8bitgentleman/activitywatch-mcp-server>

## 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": "8bitgentleman-activitywatch"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/8bitgentleman-activitywatch` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/8bitgentleman-activitywatch/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