# super-productivity-mcp

> super-productivity-mcp — kailasas-auspicious-super-productivity-mcp. Use this tool when you need to manage tasks, projects, and time tracking efficiently, and want to interact with Super Productivity's local REST API through natural language inputs. It solves problems of task organization and time management by providing a convenient interface for creating, updating, and tracking tasks and projects. The tool accepts natural language commands as input and outputs managed tasks, projects, and time tracking data, making it ideal for users seeking a streamlined productivity workflow.

Canonical page: https://skillsregistry.net/skills/kailasas-auspicious-super-productivity-mcp  
JSON: https://api.skillsregistry.net/v1/skills/kailasas-auspicious-super-productivity-mcp

## Description

Enables interaction with Super Productivity's local REST API to manage tasks, projects, and time tracking through natural language.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** productivity
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/c264ld2zja)
- **Repository:** <https://github.com/kailasas-auspicious/super-productivity-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": "kailasas-auspicious-super-productivity-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kailasas-auspicious-super-productivity-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kailasas-auspicious-super-productivity-mcp/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