YAML Workflow MCP server
Expose declarative YAML-defined workflows as MCP tools over stdio
3 stars68 downloads/wk
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YAML Workflow tools
No tool declarations could be read from the package source. They show once the server is installed.
Public scan report
scanner v0.1.9 · 2026-09-23 · same rubric, same numbers if you re-run it
- Code scan35 source files scanned25/25
- –Live reliabilityno gateway calls yet and no remote to proben/a
- –Tool poisoningtools not inspected (local package is not executed); not countedn/a
- Auth qualitylocal package, no credentials required12/15
- Maintenancelast push 2 days ago15/15
- Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
What the publisher says
From the YAML Workflow repository's README, as published. We do not edit it. Read it on GitHub
YAML Workflow
<!-- mcp-name: io.github.orieg/yaml-workflow -->
A lightweight workflow engine for CI/CD pipelines, data processing, and DevOps automation. Define reproducible, version-controlled workflows in YAML — run them locally, in CI, or on any machine with Python installed.
Why yaml-workflow?
Most workflow tools require servers, databases, and complex infrastructure. yaml-workflow takes a GitOps approach — workflows are plain YAML files, version-controlled alongside your code:
Choose yaml-workflow when you need:
- Simple task automation without infrastructure overhead
- Reproducible pipelines defined in version-controlled YAML
- Batch processing with parallel execution
- State persistence and workflow resume after failures
- A lightweight alternative to shell scripts with better error handling
- GitOps-friendly pipelines that live in your repo alongside the code
- A single tool that runs the same pipeline locally and in CI
Features
- YAML-driven workflow definition with Jinja2 templating
- Multiple task types: shell, Python, file, template, HTTP, batch
- Workflow composition via imports — reuse steps across workflows
- Plugin system via entry points — pip install yaml-workflow-myplugin
- Watch mode — --watch to re-run on file changes
- Dry-run mode to preview without executing
- Workflow visualization (ASCII branching DAG and Mermaid)
- Parallel execution with configurable worker pools
- State persistence and resume capability
- Retry mechanisms with configurable strategies
- Namespaced variables (args, env, steps, batch)
- Flow control with custom step sequences and conditions
Use Cases
- CI/CD pipelines — multi-step build, test, deploy workflows in YAML
- Data processing — batch ETL pipelines with retry and resume on failure
- DevOps automation — infrastructure tasks with secrets management and notifications
- AI/LLM pipelines — orchestrate API calls with auth, retry, and batch processing
- Local automation — replace shell scripts with reproducible, parameterized workflows
Quick Start
# Install (isolated CLI — recommended)
pipx install yaml-workflow # Core CLI
pipx install 'yaml-workflow[all]' # + web dashboard + MCP server
# Or with pip
pip install yaml-workflowShortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
Install directly
claude mcp add yaml-workflow -- uvx yaml-workflow
YAML Workflow: common questions
- Is YAML Workflow MCP server safe?
- Yes, by our scan: it is graded A (92/100). Read the YAML Workflow safety report
- How do I install YAML Workflow?
- It runs on your machine. Copy the Claude Code, Claude Desktop or Cursor config from the install section.
- Does YAML Workflow need an API key?
- Not as far as the registry entry and our scan can tell: no credentials are declared or required.
- Is YAML Workflow maintained?
- The last commit was 2 days ago (2026-09-21). The latest release is v0.9.6.