# TestDino MCP

> Use this tool when you need to analyze and optimize AI testing processes, as it enables root-cause analysis and failure pattern detection through powerful analysis capabilities. It takes test run data as input and outputs actionable insights to improve AI performance. Ideal for AI development and testing workflows, especially those integrated with git version control systems.

Canonical page: https://skillsregistry.net/skills/testdino-inc-server-12  
JSON: https://api.skillsregistry.net/v1/skills/testdino-inc-server-12

## Description

TestDino MCP boosts your AI assistant with powerful tools and analysis capabilities.
It lets your AI analyze test runs, perform root-cause analysis, and detect failure patterns.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-24

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-08-24

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/testdino-inc/server-12)

## 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": "testdino-inc-server-12"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/testdino-inc-server-12` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/testdino-inc-server-12/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