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MCP Queue Doctor

von ethanasmVersion 0.2.2i★ –iLäuft auf deinem Computer
Name in der Registryio.github.ethanasm/mcp-queue-doctor

Installieren

Überblick

Beschreibung vom Entwickler (englisches Original)

Diagnoses pg-boss and graphile-worker job queues: retry storms, stuck workers, missed schedules.

Die drei Säulen von PopNx MCP

Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

  • Verbindung: Läuft auf deinem Computer
  • Transport: stdio
  • Kategorie: Sonstiges

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Bevor du installierst

  • Basischecks: 1 von 1 bestanden
  • Läuft auf deinem Computer mit den Rechten deines Benutzerkontos (Dateien, Netzwerk, Apps).
  • Die Registry nennt keinen Schlüssel zum Eintragen.

Du brauchst

  • npmNode.js installiert (für den Befehl npx)

Welche App nutzt du?

Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.

Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein

{
  "mcpServers": {
    "queue-doctor": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-queue-doctor"
      ]
    }
  }
}

Führe das in deinem Terminal aus

claude mcp add queue-doctor -- npx -y mcp-queue-doctor

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

{
  "mcpServers": {
    "queue-doctor": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-queue-doctor"
      ]
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

In VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

{
  "servers": {
    "queue-doctor": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "mcp-queue-doctor"
      ]
    }
  }
}

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.

Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.

Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.

Was er kann

Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026

  • ✓ Bestanden

    Entwickler passt zum Repo

    Der Registry-Name wurde mit dem GitHub-Konto ethanasm bestätigt, dem das Repo gehört

  • … Noch nicht geprüft

    Wird noch gepflegt

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • … Noch nicht geprüft

    Hat eine Lizenz

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • – Nicht zutreffend

    Endpunkt antwortet

    Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet

  • – Nicht zutreffend

    Anmeldung mit OAuth

    Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen

  • … Noch nicht geprüft

    Keine versteckten Anweisungen in Tool-Beschreibungen

    Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen

Im Vergleich mit anderen in Sonstigesi

  • Mehr Sterne als 0 % der anderen 32464 Server in dieser Kategorie
  • Neuer in der Registry veröffentlicht als 22 % der anderen 32464 Server in dieser Kategorie
  • Basischecks gleich gut wie oder besser als bei 100 % der anderen 32464 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Häufige Fragen

Ist MCP Queue Doctor sicher?

Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.

Welche Schlüssel oder Codes braucht er?

Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.

Läuft er auf meinem Computer oder in der Cloud?

Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).

Wird er noch gepflegt?

Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.2.2) kam vor 3 Monaten in die Registry.

Welche Apps können ihn nutzen?

Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.

Was kann ich stattdessen nutzen?

In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, yontu

Alternativen

Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.

So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

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Läuft auf deinem Computer★ 440MITAktualisiert vor 14 Monaten
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Läuft auf deinem ComputerAktualisiert heute
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README vom Entwickler

README öffnen

Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.

mcp-queue-doctor

An MCP server that diagnoses Postgres job queues — pg-boss and graphile-worker. Retry storms, stuck workers, missed schedules, expiry overruns: what is broken, why, and the safest way to recover.

❌ "3 jobs in enrichment/corpus-fill are in state 'failed'."

✅ "enrichment/corpus-fill failed 140 times over 3m, peaking at 50 failures in a single minute. 91% share one error, which looks like an upstream rate limit. This is one fault reproduced many times, not many separate faults — so the fix belongs at the source, and retrying the jobs individually will reproduce it.

Recovery, safest first:

  1. Stop enqueuing to this queue — every new job feeds the same failure.
  2. Confirm when the upstream quota resets; treat that as the time to resume.
  3. Add a cooldown gate after N consecutive 429s. ⚠ Do NOT bulk-retry yet — the upstream is still limited.

Evidence: 140 failures, 91% 'HTTP 429 Too Many Requests (daily quota exceeded)', peak 50/min, busiest minutes [...], 12 other errors [...]"

The second answer is the product. Every finding carries the evidence it was drawn from, so you — or an agent — can check the reasoning instead of trusting it.

Where the heuristics come from

The rules are extracted from a morning health check that has run daily in production since April 2026 against a pg-boss instance driving ~30 cron queues. Every threshold was tuned by a real false positive or a real missed failure, and each rule below names the incident that motivated it. That provenance is the point: these are not heuristics invented for a README.

Install

npm install -g mcp-queue-doctor
{

"mcpServers": { "queue-doctor": { "command": "mcp-queue-doctor", "env": { "QUEUE_DOCTOR_DATABASE_URL": "postgres://readonly:pw@localhost:5432/app" } } } }

Then ask: *"Is anything wrong with my job queue?"*

Want to see it work first? examples/demo spins up a throwaway Postgres and manufactures seven failures in about a minute. It also plants a graphile-worker instance in the same database, where four of the seven rules go deliberately silent — the clearest way to see what capability declaration actually buys you.

Connecting it

The server speaks stdio, so every MCP client starts it as a subprocess. The only thing that varies is where the config lives — and whether that process can reach your database.

Claude Desktop — ~/Library/Application Support/Claude/claude_desktop_config.json on macOS, %APPDATA%\Claude\claude_desktop_config.json on Windows. Use the mcpServers block above, then restart the app.

Desktop launches its subprocesses from the app bundle, not a login shell, so PATH is minimal and a bare mcp-queue-doctor or npx often fails to resolve. Give it an absolute path — which mcp-queue-doctor after a global install, or the absolute path to npx with ["-y", "mcp-queue-doctor"] as its args.

Claude Code — one command, no file editing:

claude mcp add queue-doctor -e QUEUE_DOCTOR_DATABASE_URL=postgres://... -- npx -y mcp-queue-doctor

Add -s project to write a checked-in .mcp.json at the repo root instead of your personal config, so everyone working in that repo gets the tool.

Cloud / remote sessions (Claude Code on the web, and any other headless runner) — a checked-in .mcp.json is the only mechanism that works, because nobody is there to answer an approval prompt. Reference the connection string rather than committing it; Claude Code expands ${VAR} and ${VAR:-default} in .mcp.json:

{

"mcpServers": { "queue-doctor": { "command": "npx", "args": ["-y", "mcp-queue-doctor"], "env": { "QUEUE_DOCTOR_DATABASE_URL": "${QUEUE_DOCTOR_DATABASE_URL}" } } } }

Project-scoped servers still need to be trusted before they start. In a headless session that means setting enableAllProjectMcpServers: true in the repo's .claude/settings.json, since the interactive approval never arrives.

Reachability is the real constraint, not the config. The server runs wherever the client runs, and it connects to Postgres directly — there is no hosted component in between. A cloud sandbox can therefore only diagnose a database inside that sandbox: the demo stack, or a dev stack the session brought up itself. A production queue bound to loopback on your own host is not reachable from a sandbox at all, and exposing it to make it reachable is the wrong trade.

Diagnose production from a client on a machine that already has a route to it — your laptop, over an SSH tunnel:

ssh -N -L 5432:127.0.0.1:5432 prod-host

and point QUEUE_DOCTOR_DATABASE_URL at 127.0.0.1:5432. The tunnel is the access grant, it lasts exactly as long as the terminal stays open, and the credentials never leave your machine.

Tools

ToolAnswers
diagnoseStart here. Runs the whole rule catalog, returns ranked findings with evidence and recovery steps
queue_overviewPer-queue counts by state, stuck jobs, and each queue's expiry/retention/retry config
failed_jobsFailures in a window with error messages, plus a per-queue error-frequency breakdown
stuck_jobsJobs active past a threshold, with age, expiry, and heartbeat staleness
missed_schedulesCron queues whose latest firing is older than their expression implies
schedule_statusEvery registered schedule with cron, timezone, last firing, and next expected
job_detailOne job's full record: state, timings, retries, payload, output
server_infoConnectivity, detected schema, matched dialect, and reduced capabilities

Schedule expectations are derived from pg-boss's own schedule table by parsing each cron expression, so the common case needs no configuration. The health check this was extracted from carried a hand-maintained list of expected jobs that silently stopped covering whatever nobody remembered to add.

The rule catalog

RuleFires whenMotivating incident
retry-stormMany failures, densely packed, dominated by one errorA daily API quota tipped over and 875 corpus-fill jobs failed in one night. The count suggested 875 problems; the shape showed one
expiry-overrunFailure durations cluster at the queue's expiryA full-corpus sweep couldn't finish inside a 30-minute expiry once upstream throttling slowed it. It reported as a job failure nightly; the fix was an internal wall-clock budget
stuck-jobsJobs active far too long, or heartbeats stoppedA worker killed without graceful shutdown leaves rows active until maintenance reclaims them
missed-scheduleLatest firing predates the last expected tickDistinguishes "never fired" (scheduler never booted) from "stopped firing"
duplicate-registrationA cron queue enqueued twice for one tickAn instrumentation hook invoked job registration twice per process, so every cron ran double for weeks
retention-windowFailed-row count disagrees with the windowed countA health email stayed yellow for days after the bug was fixed, counting rows that failed days earlier
dead-queueRegistered long ago, unscheduled, holds nothingA producer that stopped, or a registration dropped in a refactor

Failures are classified (rate_limit, transient_transport, auth, not_found) because the class changes the advice: the right response to a storm of 429s is close to the opposite of the right response to connection resets.

Backends

BackendSupportVerified against
pg-boss v11+Full11.1.2 (schema 26), 12.27.0 (schema 37)
pg-boss v10Recognised, refused — see below10.4.2 (schema 24)
pg-boss v9 and earlierRecognised, refused—
graphile-worker 0.17Partial, capability-declared0.17.3

Select with QUEUE_DOCTOR_BACKEND=pgboss (default) or graphile; the schema default follows the backend.

Capabilities, not zeros

Backends don't just name columns differently — they model work differently. graphile-worker deletes a job when it succeeds, has no per-job expiry, no worker heartbeats, and keeps cron expressions in a file rather than the database. So "how many completed in the last day" has no answer there at any price.

Every backend therefore declares what it can answer, and rules that depend on missing data stay silent rather than reporting a zero — a zero reads like a measurement.

Rulepg-boss v11+graphile-worker
retry-storm✅✅
stuck-jobs✅ (with heartbeats)✅ (age only)
expiry-overrun✅— no expiry exists
missed-schedule✅— cron lives in a file
duplicate-registration✅— no firing history
retention-window✅— nothing is retained
dead-queue✅— no queue registry

server_info reports the capability set and spells out each limitation.

Versioned against pg-boss

pg-boss's tables are not a stable API. Across versions it has renamed every timestamp column (createdon → created_on), dropped a whole table (archive, removed in v11), changed a duration from an interval to an integer (expire_in → expire_seconds), partitioned the job table, and added columns (heartbeat_on) that materially change what can be diagnosed.

A tool that hard-codes one shape breaks on the next upgrade — silently, if it is unlucky. That is exactly how the health check this is extracted from spent weeks emitting a confident, wrong "missed schedules" warning that was really SQLSTATE 42P01 after pgboss.archive disappeared.

So schema knowledge lives in one file, src/pgboss/dialect.ts, as data:

  • Every relation and column name is declared in a dialect. Query builders emit identifiers from it, so supporting a new pg-boss layout is an edit to that file — no SQL elsewhere mentions a pg-boss table by name.
  • Dialects are matched on observed shape, not on a version number. pg-boss's release→schema-version mapping is not published as a contract, and a guessed mapping would reintroduce the very failure this guards against. The version integer is read, reported, and used to say *"this is newer than anything we have verified"* — but it never decides which SQL runs.
  • Optional columns are feature-detected. No heartbeat_on? Stuck-job detection degrades to age-based and says so, instead of failing.
  • Unknown layouts are refused, by name. A pre-v10 schema is recognised specifically and rejected with the reason, because diagnosing it against modern queries would silently miss every archived job. A wrong diagnosis is worse than a refusal.

server_info reports the matched dialect, the schema version, whether that version has been *verified* against real pg-boss, and any reduced capabilities.

This is not a theoretical concern — it has already caught a real bug. The dialect originally claimed a v10 floor, on the belief that v10 removed the archive table. Booting pg-boss 10.4.2 showed the archive table still present and expiry still an expire_in interval, so the dialect was rejecting v10 outright and matching nothing at all for it. The real floor is v11, and v10 now has its own dialect: recognised, and refused by name, because reading the job table alone on v10 silently misses everything already archived.

CI keeps this honest. The integration suite boots pg-boss 10, 11 and 12 into separate schemas and asserts that the observed schema version appears in the dialect's verified list — so a future pg-boss that changes the schema fails loudly rather than running unverified SQL.

Read-only, by construction

Every query runs inside a BEGIN READ ONLY transaction with a statement_timeout

Nur der Anfang wird gezeigt; den Rest findest du im Repo

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