Ross ROSS = Recommend OSS · open-source software intelligence for agents

dagucloud/dagu

Self-hostable workflow orchestrator for teams whose main work isn't orchestration. Declarative YAML over your scripts, SSH commands, containers, etc; keep workflows separate from business logic. One binary, no database, runs on limited H/W resources. Alternative to Airflow / Cron / Job Scheduler. observed · 2026-08-28

github.com/dagucloud/dagu · homepage · Go · GPL-3.0 (copyleft) observed · 2026-08-28

Health v2 · maintenance only

95/100

  • Activity 99
  • Release rhythm 87
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 1.0
  • age_days: 1594
  • days_rel: 8
  • days_push: 7
  • n_releases_24m: 173

Full methodology

Adoption not part of the score

3808 stars · 317 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Dagu is a self-hostable, local-first workflow orchestrator that runs DAGs defined in declarative YAML over existing shell scripts, Docker containers, Kubernetes Jobs, SSH commands, and HTTP/SQL calls. It ships as a single Go binary with a built-in Web UI, cron scheduling, retries, human tasks, run history, and an MCP server, requiring no external database or message broker.

Use cases

  • schedule nightly data pipeline jobs with retries and dependencies
  • replace cron jobs with a workflow engine that has logs and run history
  • orchestrate docker containers and kubernetes jobs from yaml
  • run remote commands over ssh on a fleet of servers
  • add human approval steps to automated workflows
  • control and inspect workflows from an ai agent via mcp
  • self-host a lightweight airflow alternative on limited hardware

When to choose

  • you want scheduling, retries, and dependencies around existing scripts without rewriting them into a framework
  • you need a single-binary, no-database orchestrator for on-prem, air-gapped, or edge environments
  • your team's main work isn't orchestration and you want a simple web UI over cron
  • you want to trigger or monitor workflows from LLM agents via MCP

When to avoid

  • you need a large ecosystem of prebuilt connectors and a rich Python DSL like Airflow's
  • you require enterprise features such as SSO, RBAC, or audit logging without a paid license
  • you need a fully managed cloud orchestration service

Facets

application · maturity active

workflow-automation scheduling webhook mcp cli developer-tools self-hosted developer-tools windows self-hosted go cli workflow-engine dag cron-scheduler airflow-alternative job-scheduler yaml-workflows single-binary no-database human-in-the-loop durable-execution mcp-server web-ui ssh-execution data-pipelines automation devops data-engineering ai-agents linux macos docker kubernetes

10 sources

Member repositories

RepositoryRoleHealth v2
dagucloud/dagumain95

For agents

markdown · JSON · MCP: product_card(name="dagucloud/dagu")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem