Tells AI agents which files to test first — churn, coverage, and test mapping as risk scores.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"io-github-muratkus-qaradar": {
"command": "<see-readme>",
"args": []
}
}
}Are you the author?
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Tells AI agents which files to test first — churn, coverage, and test mapping as risk scores.
No automated test available for this server. Check the GitHub README for setup instructions.
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Give your AI coding agent the quality brain it doesn't have to grow from scratch.
QA Radar analyzes your codebase and produces a structured quality health report — combining git churn, test coverage, and test-to-source mapping into risk-scored modules. It works as an MCP server for AI coding agents (Claude Code, Cursor, Windsurf) and as a standalone CLI for humans and CI pipelines.
Built for developers who want their AI agent to write targeted tests, not generic ones.
Claude Code — one step:
/plugin marketplace add Muratkus/qaradar
/plugin install qaradar@qaradar-marketplace
Then ask your agent: "What should I test first?"
Or run directly without installing:
uvx qaradar serve
QA Radar answers the question every new team member (and every AI agent) asks: "What should I test first?"
It scans three signals and combines them into a per-file risk score:
| Signal | What It Measures | Why It Matters |
|---|---|---|
| Git Churn | Commit frequency, lines changed, recency | High-churn files are regression magnets |
| Coverage Gaps | Line & branch coverage from existing reports | Low coverage = blind spots |
| Test Mapping | Which source files have corresponding tests | No tests = no safety net at all |
The output is a ranked list of modules by risk level (critical → low), with human-readable reasons for each rating.
A capable agent with bash access could run git log --numstat, parse coverage.xml, and glob for test files. So why an MCP server?
| Concern | What QA Radar does instead |
|---|---|
| Token cost | git log over 90 days on a medium repo is hundreds of KB. QA Radar returns ~5 KB of structured JSON. |
| Determinism | A weighted risk score computed ad-hoc in-context is unreliable. Code is reproducible. |
| Speed | One tool call vs. 4–6 sequential bash calls + reasoning between each. |
| Format normalization | LCOV / Cobertura / coverage.py JSON / Go cover profiles all parse differently. QA Radar normalizes across formats so the agent doesn't have to. |
| Convention encoding | test_x.py for Python, x.test.ts for JS/TS, x_test.go for Go, FooTest.java for Java — encoded once, not re-derived each session. |
| Portability | The same MCP tools work across Claude Code, Cursor, and Windsurf without re-prompting. |
The fastest path — one command wires up the MCP server and installs 4 slash commands. No manual config editing.
Step 0 — install uv (if you don't have it):
curl -LsSf https://astral.sh/uv/install.sh | sh
# or: pip install uv
uv launches qaradar on demand from PyPI — you don't need to pip install qaradar separately.
Step 1 — add the marketplace:
/plugin marketplace add Muratkus/qaradar
Step 2 — install:
/plugin install qaradar@qaradar-marketplace
What you get: 6 MCP tools auto-configured + 5 slash commands:
| Command | What it does |
|---|---|
/qaradar:qa-check | Full health report — risk, coverage, untested files |
/qaradar:qa-risky | Ranked list of riskiest files with reasons |
/qaradar:qa-untested | Source files with no detected tests + scaffold suggestions |
/qaradar:qa-plan | Prioritized test plan (chains 3 tools) |
/qaradar:qa-pr-risk | Which changed files in this PR are riskiest |
Example: after merging a big feature branch, run /qaradar:qa-check to see what regressed. Before opening a PR, run /qaradar:qa-pr-risk to see what you need to test first.
Alternative: manual MCP config (if you prefer not to use the plugin):
Add to your Claude Code MCP config (~/.claude/mcp.json for user-level, or .mcp.json in t