# testing-mcp

> testing-mcp — mcpland-testing-mcp. Use this tool when you need to automate end-to-end integration testing for your applications, leveraging large language models (LLMs) to author tests. It solves the problem of manual test creation, reducing development time and increasing test coverage. The tool integrates with git, taking in application code and outputting comprehensive integration tests.

Canonical page: https://skillsregistry.net/skills/mcpland-testing-mcp  
JSON: https://api.skillsregistry.net/v1/skills/mcpland-testing-mcp

## Description

Let LLMs author your integration tests—E2E-style.

## Trust

- **Trust score (0–1):** 0.62
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/mcpland/testing-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": "mcpland-testing-mcp"
    }
  }
}
```

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