# mcp-jest

> mcp-jest — reallyartificial-mcp-jest. Use this tool when you need to automate testing for Model Context Protocol servers to ensure their reliability and functionality. It solves problems related to manual testing and debugging, providing confidence in deploying MCP servers. The tool integrates with git, taking in MCP server code as input and outputting test results to verify server performance.

Canonical page: https://skillsregistry.net/skills/reallyartificial-mcp-jest  
JSON: https://api.skillsregistry.net/v1/skills/reallyartificial-mcp-jest

## Description

Automated testing for Model Context Protocol servers. Ship MCP Servers with confidence.

## Trust

- **Trust score (0–1):** 0.59
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/ReallyArtificial/mcp-jest)

## 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": "reallyartificial-mcp-jest"
    }
  }
}
```

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