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OSOP MCP Server

Enables AI agents to manage OSOP workflows by providing tools for validation, execution, testing, and optimization. It also supports converting workflows between OSOP and external formats like GitHub Actions, BPMN, and Airflow DAGs.

glama
Updated
Apr 1, 2026

OSOP MCP Server

License Python OSOP Compatible

MCP (Model Context Protocol) server that exposes OSOP workflow operations as tools for AI agents. Any MCP-compatible client (Claude Desktop, Claude Code, OpenClaw, Cursor, etc.) can validate, run, render, test, optimize, and assess security risks of OSOP workflows.

Website: osop.ai | Editor: osop-editor.vercel.app

Tools

ToolDescription
osop.validateValidate an .osop.yaml file against the OSOP schema. Returns errors and warnings.
osop.risk_assessAnalyze workflow for security risks — permission gaps, missing approval gates, destructive commands, cost exposure. Returns risk score (0-100) and actionable findings.
osop.runExecute a workflow with given inputs. Supports dry-run mode.
osop.renderRender a workflow as Mermaid or ASCII diagram.
osop.testRun test cases defined in the workflow and report pass/fail results.
osop.optimizeAnalyze a workflow for redundancies, parallelization opportunities, and bottlenecks.
osop.reportGenerate HTML or text reports from workflow + optional execution log.
osop.importConvert external formats (GitHub Actions, BPMN, Airflow DAG) into OSOP.
osop.exportConvert an OSOP workflow to an external format.

Installation

pip install osop-mcp

Usage

Standalone

python -m osop_mcp

The server listens on stdio by default (MCP standard transport).

Docker

docker build -t osop-mcp .
docker run -i osop-mcp

Claude Desktop / Claude Code

Add to your claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%/Claude/):

{
  "mcpServers": {
    "osop": {
      "command": "python",
      "args": ["-m", "osop_mcp"],
      "env": {}
    }
  }
}

For Claude Code, add to your project's .mcp.json:

{
  "mcpServers": {
    "osop": {
      "command": "python",
      "args": ["-m", "osop_mcp"]
    }
  }
}

Docker-based Configuration

{
  "mcpServers": {
    "osop": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "osop-mcp"]
    }
  }
}

Quick Start: Risk Assessment

Once installed, ask your AI agent:

"Analyze the security risks of my deployment workflow"

The agent will use osop.risk_assess to:

  1. Walk the workflow DAG and identify high-risk nodes
  2. Check for missing approval gates before destructive operations
  3. Flag overly broad permissions (write:*, admin:*)
  4. Detect destructive CLI commands (rm -rf, kubectl delete, terraform destroy)
  5. Calculate cost exposure from agent nodes
  6. Return a risk score (0-100) with verdict: safe / caution / warning / danger

Example output:

{
  "overall_score": 72,
  "verdict": "danger",
  "total_findings": 5,
  "findings": [
    {
      "severity": "critical",
      "title": "CRITICAL risk node without approval gate",
      "node_id": "deploy-prod",
      "suggestion": "Add approval_gate with required: true before this node."
    }
  ]
}

Environment Variables

VariableDescriptionDefault
OSOP_MCP_TRANSPORTTransport protocol (stdio or sse)stdio
OSOP_MCP_PORTPort for SSE transport8080
OSOP_LOG_LEVELLogging levelINFO

Development

git clone https://github.com/Archie0125/osop-mcp.git
cd osop-mcp
pip install -e ".[dev]"
pytest

What is OSOP?

OSOP (Open Standard Operating Protocol) is the OpenAPI of workflows. It standardizes how workflows, SOPs, and automation pipelines are defined, validated, and executed — across AI agents, CI/CD tools, and enterprise processes.

License

Apache License 2.0 — see LICENSE for details.

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