# qasphere-mcp

> Use this tool when you need to integrate Large Language Models with test management systems, enabling AI-powered development workflows and automated test case discovery. It allows models to interact directly with test cases, streamlining the development process and improving testing efficiency. Ideal for use cases requiring seamless communication between AI models and test management systems.

Canonical page: https://skillsregistry.net/skills/hypersequent-qasphere-mcp  
JSON: https://api.skillsregistry.net/v1/skills/hypersequent-qasphere-mcp

## Description

QA Sphere MCP server that enables Large Language Models to interact directly with test management system test cases, supporting AI-powered development workflows and test case discovery.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-04-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/gt0mv3t8tx)
- **Repository:** <https://github.com/Hypersequent/qasphere-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": "hypersequent-qasphere-mcp"
    }
  }
}
```

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