io.github.CloudCorpRecords/flakyguard

Official registry Other

Flaky-test evidence tracker: per-test pass/fail history, flakiness rates, and a quarantine list.

What can you do with io.github.CloudCorpRecords/flakyguard?

  • analyze_test_flakiness — Analyze test flakiness

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

NPM package @reneturcios/flakyguard
Claude Code
claude mcp add flakyguard -- npx -y @reneturcios/flakyguard@0.1.0 mcp
JSON configuration (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "flakyguard": {
            "command": "npx",
            "args": [
                "-y",
                "@reneturcios/flakyguard@0.1.0",
                "mcp"
            ]
        }
    }
}
OCI package ghcr.io/cloudcorprecords/flakyguard:0.1.0
Claude Code
claude mcp add flakyguard -- docker run -i --rm ghcr.io/cloudcorprecords/flakyguard:0.1.0 mcp
JSON configuration (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "flakyguard": {
            "command": "docker",
            "args": [
                "run",
                "-i",
                "--rm",
                "ghcr.io/cloudcorprecords/flakyguard:0.1.0",
                "mcp"
            ]
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. flakyguard
  2. CLI
  3. MCP server
  4. Docker
  5. Development
  6. License

flakyguard

"That test is flaky" is usually a feeling. flakyguard turns it into evidence. Feed it the per-test outcomes from a set of CI runs and it builds the record for every test:

  • Per-test history — how many runs contained the test, and how many times it passed, failed, or was skipped
  • Evidence runs — passes plus failures; a skip is recorded but never counts as evidence, because a test that did not run proves nothing either way
  • Classification — a test needs a minimum amount of evidence (two evidence runs by default) before it earns a verdict: stable_pass if it never failed, stable_fail if it never passed, flaky if it did both, and insufficient_data until then
  • Flakiness rate — the minority outcome's share of the evidence runs, so a test that splits its results evenly rates 0.5 and a mostly reliable one rates close to 0
  • Quarantine list — the flaky tests whose rate meets the quarantine threshold (0.5 by default), worst first, each entry carrying the pass/fail counts behind its rate
  • Verdict — quarantine_recommended when the list is non-empty, otherwise clean

Rates are rounded to four decimal places. Everything is computed locally from the runs you supply: no network, no configuration, no history kept between calls. Bad input — a run with no results, a status outside passed / failed / skipped, the same test twice in one run — is rejected with an error naming the offending path, and no partial analysis is produced.

CLI

npx @reneturcios/flakyguard analyze --input args.json
npx @reneturcios/flakyguard --version

args.json contains the full arguments object:

{
  "runs": [
    {
      "run_id": "run-101",
      "results": [
        { "test": "checkout totals", "status": "passed" },
        { "test": "search ranking", "status": "failed" }
      ]
    },
    {
      "run_id": "run-102",
      "results": [
        { "test": "checkout totals", "status": "failed" },
        { "test": "search ranking", "status": "failed" }
      ]
    }
  ],
  "min_runs": 2,
  "quarantine_threshold": 0.5
}

min_runs and quarantine_threshold are optional. The analysis is printed as JSON.

Exit codes: 0 on success, 1 on a runtime error (including an unreadable or invalid input file, or invalid input), 2 on a usage error.

MCP server

npx -y @reneturcios/flakyguard mcp

MCP client config:

{
  "mcpServers": {
    "flakyguard": {
      "command": "npx",
      "args": ["-y", "@reneturcios/flakyguard", "mcp"]
    }
  }
}
Tools
  • analyze_test_flakiness — Analyze test flakiness across CI runs.

    • runs (array, required, at least one) — runs as {run_id, results} objects, where each result is {test, status} and status is one of passed, failed, skipped; a test may not appear twice in one run
    • min_runs (integer, optional, >= 1, default 2) — minimum evidence runs before a test is classified as stable or flaky
    • quarantine_threshold (number, optional, 0 to 1, default 0.5) — flakiness-rate threshold for the quarantine list

    Returns {run_count, test_count, tests, quarantine, summary, verdict}.

Docker

docker run -i ghcr.io/cloudcorprecords/flakyguard
docker run --rm -v "$PWD:/w" ghcr.io/cloudcorprecords/flakyguard analyze --input /w/args.json

Development

npm install
npm run build   # tsc -> dist/
npm test        # tsx --test test/*.test.ts (pure local, no network)
npm run dev     # run the CLI from source

License

MIT — Copyright (c) 2026 Rene Turcios

Frequently asked questions

What is io.github.CloudCorpRecords/flakyguard?

Flaky-test evidence tracker: per-test pass/fail history, flakiness rates, and a quarantine list.

How do I install io.github.CloudCorpRecords/flakyguard?

It runs on your machine. In Claude Code: claude mcp add flakyguard -- npx -y @reneturcios/flakyguard@0.1.0 mcp. For other clients, paste the JSON configuration from this page into their MCP settings.

Does io.github.CloudCorpRecords/flakyguard need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is io.github.CloudCorpRecords/flakyguard open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains io.github.CloudCorpRecords/flakyguard?

It is published by CloudCorpRecords. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.