Systemonomic

Systemonomic

Model work domains using Cognitive Work Analysis, score tasks for AI suitability, and design organisations.

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README

Systemonomic MCP Servers

<!-- mcp-name: io.github.TonyC23/systemonomic-mcp -->

MCP (Model Context Protocol) servers that expose Systemonomic's Work Domain Analysis, ATSS assessment, and organizational design capabilities to AI agents (Claude Desktop, Cursor, Claude Code, etc.).

Quick Start

1. Install

pip install systemonomic-mcp

2. Get an API Key

  1. Log in to Systemonomic
  2. Go to Profile → API Keys
  3. Click Generate API Key
  4. Copy the key (starts with sk_sys_) — it's shown only once

3. Configure

Set the environment variable:

export SYSTEMONOMIC_API_KEY="sk_sys_your_key_here"

Optionally, point to a different API endpoint (defaults to production):

export SYSTEMONOMIC_API_URL="https://your-dev-backend.up.railway.app"

4. Add to Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "systemonomic-wda": {
      "command": "python",
      "args": ["-m", "systemonomic_mcp.wda_server"],
      "env": {
        "SYSTEMONOMIC_API_KEY": "sk_sys_your_key_here"
      }
    },
    "systemonomic-atss": {
      "command": "python",
      "args": ["-m", "systemonomic_mcp.atss_server"],
      "env": {
        "SYSTEMONOMIC_API_KEY": "sk_sys_your_key_here"
      }
    },
    "systemonomic-org": {
      "command": "python",
      "args": ["-m", "systemonomic_mcp.org_server"],
      "env": {
        "SYSTEMONOMIC_API_KEY": "sk_sys_your_key_here"
      }
    }
  }
}

5. Add to Cursor

In Cursor Settings → MCP Servers, add each server:

  • Name: systemonomic-wda
  • Command: python -m systemonomic_mcp.wda_server
  • Environment: SYSTEMONOMIC_API_KEY=sk_sys_...

Repeat for atss_server and org_server.

Available Servers

systemonomic-wda — Work Domain Analysis

Tool Description
list_projects List all projects
get_project_state Get complete project state
create_project Create a new project
get_project_stats Get project statistics
list_wda_nodes List WDA nodes
create_wda_node Create a node at a WDA level
update_wda_node Update a node's label/level/description
delete_wda_node Delete a node
list_wda_links List means-ends links
create_wda_link Link two nodes
delete_wda_link Remove a link
generate_wda AI-generate a full WDA from a text description
export_project Export project as JSON
import_wda Import nodes and links

systemonomic-atss — Assessment & Tasks

Tool Description
list_tasks List project tasks
create_task Create a task
generate_tasks_from_wda Auto-generate tasks from WDA Objects
derive_task_suggestions AI-derived task suggestions
list_suggestions List pending suggestions
accept_suggestions Promote suggestions to tasks
run_atss_batch Run ATSS assessment on all tasks
get_atss_results Get stored assessment results
persist_atss_results Save assessment results
list_atss_runs List assessment run history

systemonomic-org — Organizational Design

Tool Description
get_org_design Get current roles, org units, allocations
persist_org_design Save org design
propose_restructure AI-generated restructure proposal
apply_proposal Apply a restructure proposal
validate_raci Validate RACI matrix
create_org_snapshot Create version snapshot
list_org_snapshots List snapshots
export_org_design_json Export as JSON
generate_pdf_report Generate comprehensive PDF report
get_report_status Check report readiness

Example Conversations

"Help me model our procurement process"

You: Generate a WDA for our university procurement department. They handle purchase requests, vendor management, contract negotiation, and compliance with government regulations.

Claude: Uses create_project → generate_wda → returns the generated hierarchy

"Assess which tasks can be automated"

You: For the procurement project, derive tasks from the WDA and run an automation assessment.

Claude: Uses generate_tasks_from_wda → run_atss_batch → summarizes automation candidates

"Generate the full report"

You: Create a PDF report for the procurement project.

Claude: Uses generate_pdf_report → saves the PDF

Development

# Run a server locally for testing
cd mcp
pip install -e .
SYSTEMONOMIC_API_KEY=sk_sys_... python -m systemonomic_mcp.wda_server

# Use the MCP inspector
SYSTEMONOMIC_API_KEY=sk_sys_... mcp dev src/systemonomic_mcp/wda_server.py

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