Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Diagnoses pg-boss and graphile-worker job queues: retry storms, stuck workers, missed schedules.
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"queue-doctor": {
"command": "npx",
"args": [
"-y",
"mcp-queue-doctor"
]
}
}
}Run this in your terminal
claude mcp add queue-doctor -- npx -y mcp-queue-doctorPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"queue-doctor": {
"command": "npx",
"args": [
"-y",
"mcp-queue-doctor"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"queue-doctor": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"mcp-queue-doctor"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account ethanasm, which owns the repo
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This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
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It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.2.2) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, Python MCP
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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:
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.
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.
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.
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.
| Tool | Answers |
|---|---|
diagnose | Start here. Runs the whole rule catalog, returns ranked findings with evidence and recovery steps |
queue_overview | Per-queue counts by state, stuck jobs, and each queue's expiry/retention/retry config |
failed_jobs | Failures in a window with error messages, plus a per-queue error-frequency breakdown |
stuck_jobs | Jobs active past a threshold, with age, expiry, and heartbeat staleness |
missed_schedules | Cron queues whose latest firing is older than their expression implies |
schedule_status | Every registered schedule with cron, timezone, last firing, and next expected |
job_detail | One job's full record: state, timings, retries, payload, output |
server_info | Connectivity, 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.
| Rule | Fires when | Motivating incident |
|---|---|---|
retry-storm | Many failures, densely packed, dominated by one error | A daily API quota tipped over and 875 corpus-fill jobs failed in one night. The count suggested 875 problems; the shape showed one |
expiry-overrun | Failure durations cluster at the queue's expiry | A 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-jobs | Jobs active far too long, or heartbeats stopped | A worker killed without graceful shutdown leaves rows active until maintenance reclaims them |
missed-schedule | Latest firing predates the last expected tick | Distinguishes "never fired" (scheduler never booted) from "stopped firing" |
duplicate-registration | A cron queue enqueued twice for one tick | An instrumentation hook invoked job registration twice per process, so every cron ran double for weeks |
retention-window | Failed-row count disagrees with the windowed count | A health email stayed yellow for days after the bug was fixed, counting rows that failed days earlier |
dead-queue | Registered long ago, unscheduled, holds nothing | A 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.
| Backend | Support | Verified against |
|---|---|---|
| pg-boss v11+ | Full | 11.1.2 (schema 26), 12.27.0 (schema 37) |
| pg-boss v10 | Recognised, refused — see below | 10.4.2 (schema 24) |
| pg-boss v9 and earlier | Recognised, refused | — |
| graphile-worker 0.17 | Partial, capability-declared | 0.17.3 |
Select with QUEUE_DOCTOR_BACKEND=pgboss (default) or graphile; the schema default follows the backend.
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.
| Rule | pg-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.
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:
heartbeat_on? Stuck-job detection degrades to age-based and says so, instead of failing.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.
Every query runs inside a BEGIN READ ONLY transaction with a statement_timeout
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