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Local-first workflow engine with a Web UI for small teams. Define DAGs in a declarative YAML format. Self-contained and no DBMS required. Use any AI agent to manage your DAGs.

MCP Servers3.5k stars282 forksGoGPL-3.0Updated today
Editor's note

Dagu is a self-contained, file-backed workflow orchestration engine written in Go that lets teams define directed acyclic graphs (DAGs) in declarative YAML and run them via a built-in Web UI without requiring a database like PostgreSQL or a message broker. Steps can execute shell commands, Docker containers, Kubernetes Jobs, SSH remote commands, and AI agent harnesses, all managed through a single binary that installs on Linux, macOS, or Windows. It connects to Claude and other AI agents through a built-in MCP server, allowing agents to create, trigger, monitor, and manage workflows programmatically. The Web UI provides a kanban-style cockpit view, per-step logs, retry controls, and human-in-the-loop approval steps. A standout detail is that Dagu stores all state in local files rather than an external DBMS, making it practical for edge deployments, private infrastructure, and small teams who want Airflow-style DAG orchestration without the six-plus service overhead traditional orchestrators require. DevOps engineers, data engineers, and support teams managing cron jobs or ETL pipelines benefit most.

ClaudeWave Trust Score
100/100
Verified
Passed
  • Open-source license (GPL-3.0)
  • Actively maintained (<30d)
  • Healthy fork ratio
  • Clear description
  • Topics declared
  • Mature repo (>1y old)
Last scanned: 6/11/2026
Install in Claude Code / Claude Desktop
Method: Manual · dagu
Claude Code CLI
git clone https://github.com/dagucloud/dagu
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "dagu": {
      "command": "dagu"
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
💡 Install the binary first: go install github.com/dagucloud/dagu@latest (make sure it ends up on your PATH).
Use cases

MCP Servers overview

README preview not available. Visit the repo on GitHub for full documentation.
agentic-workflowcrondata-pipelinedevopsdurable-executiondurable-workflowshuman-in-the-loopjob-schedulermcp-servermultiplayer-agenton-premiseprivate-runnersself-hostedself-serviceselfservice-portaltask-automationtask-schedulerworkflow-engineworkflow-orchestrationworkflow-scheduler

What people ask about dagu

What is dagucloud/dagu?

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dagucloud/dagu is mcp servers for the Claude AI ecosystem. Local-first workflow engine with a Web UI for small teams. Define DAGs in a declarative YAML format. Self-contained and no DBMS required. Use any AI agent to manage your DAGs. It has 3.5k GitHub stars and was last updated today.

How do I install dagu?

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You can install dagu by cloning the repository (https://github.com/dagucloud/dagu) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is dagucloud/dagu safe to use?

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Our security agent has analyzed dagucloud/dagu and assigned a Trust Score of 100/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.

Who maintains dagucloud/dagu?

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dagucloud/dagu is maintained by dagucloud. The last recorded GitHub activity is from today, with 115 open issues.

Are there alternatives to dagu?

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Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.

Deploy dagu to your cloud

Ship this repo to production in minutes. Each platform spins up its own environment with editable env vars.

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