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musharna/jobd

by Various

Self-hostable GPU-aware job broker for your own machines, with native MCP/agent integration

MCP

musharna/jobd

Added 11 June 2026

#distributed-systems #fastapi #gpu #homelab #job-queue #job-scheduler #mcp #self-hosted

Overview

jobd is a self-hostable job broker that manages GPU-aware workloads across your own machines. It uses a Python queue system and provides native MCP/agent integration for coordinating distributed tasks.

Best for

Best for
Developers needing a private, GPU-aware job broker that can plug into agent systems

Use cases

  • Distribute GPU-intensive jobs across a cluster of local machines
  • Integrate job queuing into agent workflows via MCP protocol
  • Run batch processing tasks with dynamic resource awareness

How to use

Install

pip install jobd "jobd[mcp]" "jobd[worker]"

Tools exposed

  • jobd
  • job
  • jobd-mcp
  • jobd-worker

Tested with

Claude Code

Notes

jobd is a self-hostable job broker that manages GPU-aware workloads across your own machines. It uses a Python queue system and provides native MCP/agent integration for coordinating distributed tasks.

0 stars on GitHub. Last updated 2026-06-11. Licensed MIT.

Use cases

  • Distribute GPU-intensive jobs across a cluster of local machines
  • Integrate job queuing into agent workflows via MCP protocol
  • Run batch processing tasks with dynamic resource awareness

Pros

  • Self-hosted, keeping data and jobs on your own infrastructure
  • GPU-aware scheduling for optimal resource utilization
  • MCP integration enables easy agent-based orchestration

Cons

  • No public star count suggests limited community adoption or validation
  • Python-only codebase may restrict non-Python environments
  • Requires manual setup and maintenance of the broker infrastructure

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Self-hosted, keeping data and jobs on your own infrastructure
  • GPU-aware scheduling for optimal resource utilization
  • MCP integration enables easy agent-based orchestration

Cons

  • No public star count suggests limited community adoption or validation
  • Python-only codebase may restrict non-Python environments
  • Requires manual setup and maintenance of the broker infrastructure

Pairs with

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