# jobd 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](https://manpages.ubuntu.com/manpages/noble/man1/tsp.1.html) or [pueue](https://github.com/Nukesor/pueue), but across all your machines on [Tailscale](https://tailscale.com/) or a LAN, routing each job to a worker with the VRAM free, with no cloud, Kubernetes or Slurm. [![CI](https://img.shields.io/github/actions/workflow/status/musharna/jobd/ci.yml?branch=main&label=CI)](https://github.com/musharna/jobd/actions/workflows/ci.yml) [![PyPI](https://img.shields.io/pypi/v/jobd)](https://pypi.org/project/jobd/) [![Python](https://img.shields.io/pypi/pyversions/jobd)](https://pypi.org/project/jobd/) [![License](https://img.shields.io/pypi/l/jobd)](https://github.com/musharna/jobd/blob/main/LICENSE) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.21636369.svg)](https://doi.org/10.5281/zenodo.21636369) [![Glama](https://glama.ai/mcp/servers/musharna/jobd/badges/score.svg)](https://glama.ai/mcp/servers/musharna/jobd)

jobd in action: job fleet status shows four workers and their versions; a GPU job routes to the worker with enough free VRAM and streams back; a stdin batch submits two jobs at once; job logs -f follows one to completion

```bash # from any machine on your tailnet: job submit --project myproj --gpu --vram-required 16 --wait -- python train.py # → routed to whichever worker has ≥16 GB VRAM free, streamed back to your terminal ``` VRAM routing tracks one GPU per host: the worker reports free memory on GPU index 0 only. ## Why it exists - **VRAM-fit routing.** Each job goes to a worker whose live free VRAM, RAM, CPUs, capability tags and arch/OS fit it, instead of you guessing which box is free. - **Preemption with a checkpoint window.** A higher-priority job can preempt a running one: `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](https://github.com/musharna/jobd/blob/main/docs/preemption.md)). - **Survives sessions.** Jobs live in the broker, not your shell. Submit, close the laptop, check back tomorrow. - **Agent-native.** An [MCP](https://modelcontextprotocol.io/) server lets an AI agent submit, monitor and babysit jobs as tool calls ([does it help?](#does-it-help)). - **Yours.** One broker process on a machine you own. No accounts, no telemetry, no per-GPU-hour billing. Only the optional self-update scripts go online ([runbook](https://github.com/musharna/jobd/blob/main/docs/runbook.md#continuous-deployment)). ## Why not just use…? | 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 | ## Install ```bash 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. ## Quickstart (single host) ```bash # 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 # 2. in another shell, install + start a worker pointed at it pip install "jobd[worker]" JOBD_URL=http://127.0.0.1:8765 JOBD_WORKER_HOST=local jobd-worker # 3. submit a job and wait for it 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](https://github.com/musharna/jobd/blob/main/docs/security.md) and the templates in `docker-compose.yml` and `scripts/`. Adding a worker to a running fleet is one command: ```bash job fleet add user@newbox # ssh in, install pinned to the broker's version, # wire systemd units + the self-update timer, # verify it registers. `job fleet status` shows drift. ``` Day-2 operations (health, draining a worker, upgrades, token rotation, backups) are in [docs/runbook.md](https://github.com/musharna/jobd/blob/main/docs/runbook.md). ## How it works

Architecture: job CLI, jobd-mcp MCP tools, and HTTP/SSE clients talk to the jobd broker (FastAPI — queue, VRAM matcher, priorities, SQLite) over one tailnet; the broker dispatches via long-poll claims and heartbeats to workers A (24 GB GPU), B (8 GB GPU), and C (CPU-only)

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](https://github.com/musharna/jobd/blob/main/docs/ARCHITECTURE.md). ## CLI ``` 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](https://github.com/musharna/jobd/blob/main/docs/cli.md). ## MCP / agent integration `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](https://github.com/musharna/jobd/blob/main/docs/agent-cookbook.md) walks through babysitting, preemption, sweeps, and asking why a job won't schedule. For [Claude Code](https://docs.claude.com/en/docs/claude-code): ```bash claude mcp add jobd \ --env JOBD_URL=http://127.0.0.1:8765 \ --env JOBD_API_TOKEN= \ -- jobd-mcp ``` Any other MCP client: ```json { "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. ## Does it help? Equally accurate, and faster and cheaper: on 38 harder questions about a live broker, Claude answered 38 right in all 3 runs with jobd-mcp and 37 with the `job` CLI, a pre-registered tie (McNemar p = 1).

Bar chart of right and wrong answers to 38 questions about a live jobd broker, 3 runs per question for each Claude setup. Constant guess with no model: 3 right, 35 wrong. Best constant fit to the answer key: 9 right, 29 wrong. Claude with the job CLI: 113 right, 1 wrong. Claude with jobd-mcp: 114 of 114 right.

With the server the 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. Method, controls and limitations: [benchmarks/agent_qa](https://github.com/musharna/jobd/blob/main/benchmarks/agent_qa/README.md). ## Supported platforms | 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. ## Configuration - **Config files** (`projects.yaml`, `profiles.yaml`, `classifier.yaml`) are all optional and read from `JOBD_CONFIG_DIR`; see [docs/projects-yaml.md](https://github.com/musharna/jobd/blob/main/docs/projects-yaml.md). - **Environment variables:** every `JOBD_*` variable is in [docs/configuration.md](https://github.com/musharna/jobd/blob/main/docs/configuration.md). - **Concurrency** (several jobs per worker): [docs/concurrency.md](https://github.com/musharna/jobd/blob/main/docs/concurrency.md). **Retention** of logs and job records: [docs/runbook.md](https://github.com/musharna/jobd/blob/main/docs/runbook.md#joblog-retention). ## Security Run the broker on loopback or a Tailscale tailnet, never a public interface. Three stacked controls: 1. **Bind:** `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. 2. **Source IP:** requests from outside loopback and `100.64.0.0/10` get `403` (`JOBD_DISABLE_TAILNET_ACL=1` turns this off). 3. **Token:** every host sets `JOBD_API_TOKEN`; `JOBD_ALLOW_NO_AUTH=1` is for a loopback-only broker, and on any other bind exposes unauthenticated code execution to your tailnet. `/livez`, `/readyz` and `/metrics` are exempt from both the source-IP check and the token; `/metrics` shows every worker's hostname and version, so don't port-forward the broker. Threat model and token rotation: [docs/security.md](https://github.com/musharna/jobd/blob/main/docs/security.md). ## License MIT; see [LICENSE](https://github.com/musharna/jobd/blob/main/LICENSE).