# Linear Regression

> Use this tool when you need to predict continuous outcomes based on linear relationships between variables, solving problems such as forecasting, trend analysis, and data modeling. It takes in datasets with input features and target variables, and outputs predicted values and model coefficients. Ideal for use in data analysis, machine learning, and statistical modeling contexts.

Canonical page: https://skillsregistry.net/skills/heetvekariya-linear-regression  
JSON: https://api.skillsregistry.net/v1/skills/heetvekariya-linear-regression

## Description

A Python implementation of linear regression using the Model Context Protocol (MCP) framework. This project demonstrates how to apply linear regression techniques within the MCP architecture.

## Trust

- **Trust score (0–1):** 0.86
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/heetvekariya-linear-regression)
- **Repository:** <https://github.com/heetvekariya/linear-regression-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": "heetvekariya-linear-regression"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/heetvekariya-linear-regression` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/heetvekariya-linear-regression/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