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Aggregates CI failures, cross-references flakiness history, and outputs GO/NO_GO release verdicts.
Aggregates CI failures, cross-references flakiness history, and outputs GO/NO_GO release verdicts.
Valid MCP server (2 strong, 4 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry. Trust signals: trusted author (15/15 approved).
6 files analyzed Β· 1 issue found
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Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-vola-trebla-release-readiness-triage-mcp": {
"args": [
"-y",
"release-readiness-triage-mcp"
],
"command": "npx"
}
}
}From the project's GitHub README.
Stop reading CI logs. Start getting verdicts.
MCP server that aggregates test failures, cross-references flakiness history, and outputs a GO / CONDITIONAL_GO / NO_GO / INVESTIGATE release decision β so your AI agent can triage a broken CI run in seconds instead of asking you to read 3000 lines of logs.
In any real codebase, CI always has something failing. The hard question isn't "are there failures?" β it's "are these failures real regressions, or just the usual noise?"
Answering that requires correlating three signals at once:
An AI agent can't do this without structured tools. Raw CI logs are thousands of lines. Flakiness databases are external. Codeβtest mapping requires AST analysis. Without this MCP, the agent just guesses.
aggregate_suite_failuresGroups failures by normalized error signature, deduplicates repeated errors, categorizes as assertion / timeout / network / crash. Pass customInfraPatterns for cloud-specific errors.
cross_reference_flakinessScores each failure against your flakiness history: KNOWN FLAKY, MILDLY FLAKY, or NO HISTORY.
correlate_code_changesMatches changed files against failing tests. Works standalone or with pre-computed affected test lists from ast-impact-mapper-mcp.
generate_release_recommendationThe final step. Outputs a risk-weighted verdict with confidence score and full breakdown. Supports format: "markdown" for GitHub PR comments and Slack.
Verdict levels:
NO_GO β regression in a critical domain (payment, auth, billing, checkout, security)CONDITIONAL_GO β regression in a low/medium-risk domain (analytics, docs, admin); review before releasingGO β all failures are known flaky or infrastructure noiseINVESTIGATE β too many unknowns to decideOutput includes:
aggregate_risk_score β 0.0β1.0, probability union across all regression risk contributionsfailing_tests_analysis[] β per-regression breakdown with domain, severity (HIGH/MEDIUM/LOW), risk_contribution, blast_radiusdetect_temporal_failure_patternsAnalyzes historical failures with timestamps to identify chronometric artifacts β failures that only appear at the same UTC hour, weekday, day of month, or during DST transitions. When a pattern is found, the failure is a time artifact, not a code regression.
Output includes:
temporal_pattern_detected β booleanclusters[] β per-test: pattern_type (hourly | daily | monthly | timezone_shift), cluster_times, confidence_scoreanalyze_rollback_readinessScans a repository for versioned migration files (Flyway V*.sql, Prisma migration.sql, Liquibase XML/YAML) and classifies each operation as additive (rollback safe) or destructive (forward-fix only).
Detected destructive operations: DROP TABLE, DROP COLUMN, ALTER COLUMN TYPE, MODIFY COLUMN, TRUNCATE
Output includes:
rollback_eligible β booleanblocking_migrations[] β each with file, line, operation, reasondeployment_strategy β standard | forward_fix_only5 failures in CI. What's real, what's noise?
failures:
- Auth Suite > login with expired token β "Expected status 200, got 401"
- API Suite > health check β "connect ECONNREFUSED 127.0.0.1:3000"
- Button Suite > renders button correctly β "Expected null, got <button>Submit</button>"
- Search Suite > debounce timing β "Expected 42, received 43"
- Storage Suite > upload avatar β "GCP quota exceeded for this project"
changedFiles: ["src/components/Button.tsx"]
affectedTests: ["renders button correctly"]
customInfraPatterns: ["GCP quota exceeded"]
format: "markdown"
Output:
## π΄ Release Recommendation: NO_GO (75% confidence)
> 1 confirmed regression(s) in critical domain(s) [payment]. Do not release.
**Aggregate risk score:** 1.0
| Category | Count |
| ------------------- | ----- |
| Total failures | 5 |
| π΄ Real regressions | 1 |
| π‘ Known flaky | 2 |
| βͺ Infra blips | 2 |
| β Unknown | 0 |
### Risk Breakdown
| Test | Domain | Severity | Risk | Blast Radius |
| -------------------------------------- | ------ | -------- | ---- | ------------ |
| Button Suite::renders button correctly | core | MEDIUM | 0.5 | 1 |
### Blockers (must fix before release)
**Button Suite > renders button correctly**
- Test is directly affected by code changes in this commit
- `Expected null, got <button>Submit</button>`
### Safe to ignore
- ~~Auth Suite > login with expired token~~ β Historically flaky: 73% failure rate in history
- ~~API Suite > health check~~ β Error pattern matches infrastructure issues (network)
- ~~Search Suite > debounce timing~~ β Mildly flaky: 22% historical failure rate
- ~~Storage Suite > upload avatar~~ β Error pattern matches infrastructure issues (network)
One tool call. One verdict. Go fix Button.tsx.
{
"mcpServers": {
"release-readiness-triage": {
"command": "npx",
"args": ["-y", "release-readiness-triage-mcp"]
}
}
}
"Here are the failures from our CI run, our flakiness database, and the files changed in this PR. Is it safe to release?"
The agent calls generate_release_recommendation and returns a verdict with a full breakdown β ready to paste into a PR comment or Slack.
Works standalone, or as a meta-orchestrator on top of:
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