# ARPI MCP

> ARPI MCP — ai-arpi-arpi-mcp. Use this tool when you need to analyze ECG images and receive accurate diagnosis reports. It solves problems related to cardiovascular disease diagnosis, providing healthcare professionals with rapid and reliable ECG analysis. By submitting ECG images as input, users receive detailed diagnosis reports as output, making it ideal for use in clinical settings where timely and accurate diagnoses are crucial.

Canonical page: https://skillsregistry.net/skills/ai-arpi-arpi-mcp  
JSON: https://api.skillsregistry.net/v1/skills/ai-arpi-arpi-mcp

## Description

AI-powered ECG analysis: submit ECG images and receive diagnosis reports from ARPI's ECG AI.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-03

## Facts

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

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.arpi%2Farpi-mcp)
- **Repository:** <https://github.com/arpi-ai/arpi-mcp>

## Use it

MCP endpoint published by the skill: `https://mcp.arpi.ai/mcp`

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": "ai-arpi-arpi-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-arpi-arpi-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-arpi-arpi-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