# Habit Tracker MCP Server

> Use this tool when you need to monitor and analyze your daily habits and receive insights on your progress. It solves problems of habit formation, tracking, and reflection by providing a weekly review of user habits through natural language prompts. The tool takes in user habit data as input and outputs personalized weekly reviews, making it ideal for users seeking to develop consistent routines and self-awareness.

Canonical page: https://skillsregistry.net/skills/darialissi-litestar-habittracker  
JSON: https://api.skillsregistry.net/v1/skills/darialissi-litestar-habittracker

## Description

Enables users to analyze their habits over a specified period and receive weekly reviews through natural language prompts.

## 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/oiuchrezkz)
- **Repository:** <https://github.com/darialissi/litestar-habittracker>

## 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": "darialissi-litestar-habittracker"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/darialissi-litestar-habittracker` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/darialissi-litestar-habittracker/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