# data-science-mcp

> data-science-mcp — lichenstuttgart-data-science-mcp. Use this tool when you need to analyze and forecast time-series data, solving problems such as predicting trends and identifying patterns. It takes in time-stamped data as input and outputs forecasts and diagnostics, utilizing algorithms like ARIMA and AutoML. Ideal for use cases requiring data-driven insights, such as demand forecasting and resource planning.

Canonical page: https://skillsregistry.net/skills/lichenstuttgart-data-science-mcp  
JSON: https://api.skillsregistry.net/v1/skills/lichenstuttgart-data-science-mcp

## Description

Enables time-series analysis and forecasting through a structured tool catalogue, including data loading, quality repair, diagnostics, and forecasting with ARIMA, exponential smoothing, Chronos-2, Toto 2.0, and AutoML.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/m80vvl2v7c)
- **Repository:** <https://github.com/LiChenStuttgart/data-science-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": "lichenstuttgart-data-science-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/lichenstuttgart-data-science-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/lichenstuttgart-data-science-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