# key-drivers-mcp

> Use this tool when you need to analyze key drivers and feature importance in complex datasets, solving problems such as identifying influential variables and understanding relationships between them. It takes in datasets and rule mining parameters as inputs and outputs feature importance scores and key driver rankings. Ideal for use cases where understanding variable interactions and dependencies is crucial, such as predictive modeling and decision-making.

Canonical page: https://skillsregistry.net/skills/petrmasa-key-drivers-mcp  
JSON: https://api.skillsregistry.net/v1/skills/petrmasa-key-drivers-mcp

## Description

MCP server for key driver and feature importance analysis based on rule mining

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/h80xn5dvcf)
- **Repository:** <https://github.com/petrmasa/key_drivers_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": "petrmasa-key-drivers-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/petrmasa-key-drivers-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/petrmasa-key-drivers-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