About Gflow
Gflow is an MCP server in the Automation category: a lightweight, single-node GPU job scheduler implemented in Rust.
Install
git clone https://github.com/AndPuQing/gflowThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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README
gflow
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gflow is a lightweight scheduler for a single Linux machine. It brings a Slurm-like workflow to shared GPU workstations and lab servers without cluster setup.
Why gflow
- Queue and run jobs on one machine.
- Submit commands or scripts with GPUs, time limits, dependencies, arrays, and priorities.
- Inspect, attach, cancel, and recover jobs with a small CLI.
Install
Requirements: Linux, tmux, and NVIDIA drivers only if you need GPU scheduling.
Install with Python tooling:
uv tool install runqd
# or
pipx install runqd
# or
pip install runqd
Install with Cargo:
cargo install gflow
Nightly build:
pip install --index-url https://test.pypi.org/simple/ runqd
Quick Start
gflowd init
gflowd up
gbatch --gpus 1 --name demo bash -lc 'echo "hello from gflow"; sleep 30'
gqueue
gjob show <job_id>
gflowd down
MCP
gflow can also run as a local MCP server for Claude Desktop, Claude Code, Codex, Cursor, and similar tools:
gflow mcp serve
Keep gflowd running on the same machine. MCP clients start gflow mcp serve as a local stdio server.
Claude Desktop example:
Claude Code:
claude mcp add --scope user gflow -- gflow mcp serve
Codex:
codex mcp add gflow -- gflow mcp serve
Or via ~/.codex/config.toml:
[mcp_servers.gflow]
command = "gflow"
args = ["mcp", "serve"]
If gflow is not on your PATH, replace it with the absolute binary path.
Documentation
Most usage details live in the docs:
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Contact Us
For coordinating contributions and development, please use Slack
Contributing
Please open an Issue or Pull Request.
License
MIT. See LICENSE.
README copy captured when this server was indexed; it may lag the repository. The original is authoritative.