systemonomic-mcp

systemonomic-mcp

TonyC23

MCP servers for Work Domain Analysis, AI task automation scoring, and organizational design through Systemonomic platfor

MCP servers that expose Systemonomic's Work Domain Analysis, AI Task Suitability Scoring, and organizational design capabilities to AI agents for system modeling and automation assessment.

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About systemonomic-mcp

systemonomic-mcp is a community-built MCP server published by TonyC23 that provides AI assistants with tools and capabilities via the Model Context Protocol. MCP servers for Work Domain Analysis, AI task automation scoring, and organizational design through Systemonomic platfor It is categorized under ai ml. This server exposes 20 tools that AI clients can invoke during conversations and coding sessions.

How to install

You can install systemonomic-mcp in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

License

systemonomic-mcp is released under the NOASSERTION license.

Tools (20)

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

Systemonomic MCP Servers

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 ProfileAPI 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

ToolDescription
list_projectsList all projects
get_project_stateGet complete project state
create_projectCreate a new project
get_project_statsGet project statistics
list_wda_nodesList WDA nodes
create_wda_nodeCreate a node at a WDA level
update_wda_nodeUpdate a node's label/level/description
delete_wda_nodeDelete a node
list_wda_linksList means-ends links
create_wda_linkLink two nodes
delete_wda_linkRemove a link
generate_wdaAI-generate a full WDA from a text description
export_projectExport project as JSON
import_wdaImport nodes and links

systemonomic-atss — Assessment & Tasks

ToolDescription
list_tasksList project tasks
create_taskCreate a task
generate_tasks_from_wdaAuto-generate tasks from WDA Objects
derive_task_suggestionsAI-derived task suggestions
list_suggestionsList pending suggestions
accept_suggestionsPromote suggestions to tasks
run_atss_batchRun ATSS assessment on all tasks
get_atss_resultsGet stored assessment results
persist_atss_resultsSave assessment results
list_atss_runsList assessment run history

systemonomic-org — Organizational Design

ToolDescription
get_org_designGet current roles, org units, allocations
persist_org_designSave org design
propose_restructureAI-generated restructure proposal
apply_proposalApply a restructure proposal
validate_raciValidate RACI matrix
create_org_snapshotCreate version snapshot
list_org_snapshotsList snapshots
export_org_design_jsonExport as JSON
generate_pdf_reportGenerate comprehensive PDF report
get_report_statusCheck 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_projectgenerate_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_wdarun_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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