Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Self-hostable GPU-aware job broker: submit, route by VRAM, babysit jobs across machines via MCP.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
JOBD_URL, JOBD_API_TOKENLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"jobd": {
"command": "uvx",
"args": [
"jobd"
],
"env": {
"JOBD_URL": "your-value",
"JOBD_API_TOKEN": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add jobd --env JOBD_URL=your-value --env JOBD_API_TOKEN=your-value -- uvx jobdCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"jobd": {
"command": "uvx",
"args": [
"jobd"
],
"env": {
"JOBD_URL": "your-value",
"JOBD_API_TOKEN": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"jobd": {
"type": "stdio",
"command": "uvx",
"args": [
"jobd"
],
"env": {
"JOBD_URL": "your-value",
"JOBD_API_TOKEN": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
JOBD_URL envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub musharna, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
Debes completar: JOBD_API_TOKEN
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.5.52) llegó al registro hace 18 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, Excaliself
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Find, read, create, edit, and organize Excalidraw drawings in your self-hosted Excaliself instance.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
jobd is a job broker with an MCP server that lets AI agents submit, route and babysit jobs on a few machines of your own. Like task-spooler or pueue, but across all your machines on Tailscale or a LAN, routing each job to a worker with the VRAM free, with no cloud, Kubernetes or Slurm.
# from any machine on your tailnet:
job submit --project myproj --gpu --vram-required 16 --wait -- python train.py
VRAM routing tracks one GPU per host: the worker reports free memory on GPU index 0 only.
SIGTERM, a grace window for the workload to save into its JOBD_CHECKPOINT_DIR, then SIGKILL. A preempted job is not re-run; to resume, submit a new job pointed at the checkpoint (docs/preemption.md).| Tool | What it gives you | Why jobd instead |
|---|---|---|
| `nohup` / `tmux` / ssh | Runs a command on one box | No queue, VRAM-aware routing, preemption, or record of what ran where |
| [task-spooler](https://manpages.ubuntu.com/manpages/noble/man1/tsp.1.html) | A job queue on one machine | jobd queues across all your machines and routes by live VRAM/CPU fit |
| [Pueue](https://github.com/Nukesor/pueue) | A mature single-machine queue daemon | Pueue's README puts distributed execution out of scope; jobd is that layer, plus GPU awareness |
| [HyperQueue](https://github.com/It4innovations/hyperqueue) | Multi-machine scheduling with HPC roots, single binary | Counts GPUs but doesn't track VRAM; no preemption/checkpoint contract or agent interface |
| Slurm | Datacenter-grade scheduling | Heavy to stand up and operate for 2–3 personal boxes |
| SkyPilot / dstack | Runs on clouds and your own machines | SkyPilot's "existing machines" mode installs Kubernetes (k3s) on your boxes; dstack wants Docker and passwordless sudo on every host |
| Modal | Serverless GPU compute | Runs on Modal's machines, not yours |
| Ray | Distributed compute; Ray Jobs runs any shell command on a Ray cluster | You first stand up and run a Ray cluster |
pip install jobd # broker + CLI
pip install "jobd[mcp]" # adds the MCP server pip install "jobd[worker]" # adds the worker daemon (jobd-worker)
Requires Python ≥ 3.11. scripts/install-worker.sh sets up a worker under ~/jobd-worker with its own venv and a generated config.
# 1. start the broker (binds 127.0.0.1:8765 by default)
JOBD_ALLOW_NO_AUTH=1 jobd # no-auth is fine for a loopback-only broker
pip install "jobd[worker]" JOBD_URL=http://127.0.0.1:8765 JOBD_WORKER_HOST=local jobd-worker
job submit --project demo --wait -- echo hello job list job logs
For a multi-host deployment (Docker broker, systemd workers, Tailscale binding, shared auth token), see docs/security.md and the templates in docker-compose.yml and scripts/. Adding a worker to a running fleet is one command:
job fleet add user@newbox # ssh in, install pinned to the broker's version,
job fleet status shows drift.
Day-2 operations (health, draining a worker, upgrades, token rotation, backups) are in docs/runbook.md.
The broker (FastAPI + SQLite) holds the queue, runs the matcher and resolves per-project priorities. Workers, one per host, poll it, so nothing connects in to a worker: each heartbeats its live capacity, claims jobs it can run, streams logs back and honors preemption. The argv you submit runs as-is (shell=False); job submit --stdin and the MCP jobd_submit tool are the exceptions and run a command string as bash -c . Design notes: docs/ARCHITECTURE.md.
job submit -p PROJ [options] -- CMD... # queue a job
job list [--state STATE] [--project P] # queue + recent jobs job status ID | A [--watch] # one job, or an array's aggregate job logs ID [-n BYTES] # tail captured output job wait ID # block until terminal job cancel ID / job preempt ID # stop a job job adopt --pid N -p PROJ [--gpu] # track a process started outside jobd (Linux) job workers # fleet snapshot + health job projects list | set NAME PRI | nudge NAME DELTA job audit [--project P] [--since 24h] # event history
Job arrays and sweeps, --explain dry runs, job adopt, and a pueue/task-spooler command map: docs/cli.md.
jobd-mcp exposes the queue as nine tools: jobd_submit, jobd_status, jobd_logs, jobd_list, jobd_cancel, jobd_preempt, jobd_events, jobd_workers, jobd_worker_delete. docs/agent-cookbook.md walks through babysitting, preemption, sweeps, and asking why a job won't schedule.
For Claude Code:
claude mcp add jobd \
--env JOBD_URL=http://127.0.0.1:8765 \ --env JOBD_API_TOKEN= \ -- jobd-mcp
Any other MCP client:
{
"mcpServers": { "jobd": { "command": "jobd-mcp", "env": { "JOBD_URL": "http://127.0.0.1:8765", "JOBD_API_TOKEN": " " } } } }
JOBD_API_TOKEN must match the broker's token, or every call returns 401. examples/claude-code-hooks/ has optional hooks that nudge (or hard-block) an agent toward submitting heavy commands through jobd.
Claude with the server was compared with Claude using jobd's own job CLI, on 38 questions about a live broker, 3 runs each. With Claude Haiku 5.5 the server got all 38 right in every run and the CLI 29: a pre-registered win (Holm-adjusted McNemar p = 0.008). With Sonnet 5.5 it was 36 against 30 and with Opus 5.5 38 against 37, neither separated. On all three models the server's answers were cheaper and faster; with Sonnet, 0.20 times the cost and 0.17 times the time.
The chart is the Opus 5.5 run (2026-10-18). There the server's median answer cost 0.20 times as much (95% CI 0.15 to 0.28) and took 0.16 times as long (0.13 to 0.20), and it was cheaper and faster on all 38 questions. These were secondary endpoints, measured on an unreleased commit that adds a finished_at window to jobd_list. On an earlier, easier set both setups got 123 of 123.
We wrote the questions and ran the benchmark ourselves; an outside re-run is welcome. Method, controls and limitations: benchmarks/agent_qa; the Haiku and Sonnet runs: 2026-10-20 re-run.
| Component | Linux | macOS | Windows |
|---|---|---|---|
Broker (jobd) | tested | expected | expected (WSL recommended) |
CLI (job) / MCP (jobd-mcp) | tested | expected | expected |
Worker (jobd-worker) | tested | degraded | untested |
CI runs on Ubuntu with no GPU runner (VRAM paths are tested against mocks), and without a systemd user instance the worker still runs jobs but drops its memory caps, process reaping and preemption guarantees.
projects.yaml, profiles.yaml, classifier.yaml) are all optional and read from JOBD_CONFIG_DIR; see docs/projects-yaml.md.JOBD_* variable is in docs/configuration.md.Run the broker on loopback or a Tailscale tailnet, never a public interface. Three stacked controls:
JOBD_HOST is 127.0.0.1 by default; set it to a Tailscale address (100.64.0.0/10), never 0.0.0.0. The broker does not enforce this.100.64.0.0/10 get 403 (JOBD_DISABLE_TAILNET_ACL=1 turns this off).Solo se muestra el principio; lee el resto en el repo