Systemonomic — Work Domain Analysis & AI Task Suitability
Model work domains, score tasks for AI suitability, and design organisations.
Install
Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).
systemonomic-mcpclaude mcp add systemonomic-work-domain-analysis-ai-tas -e 'SYSTEMONOMIC_API_KEY=<your systemonomic_api_key>' -- uvx systemonomic-mcp==0.1.1{
"mcpServers": {
"systemonomic-work-domain-analysis-ai-tas": {
"command": "uvx",
"args": [
"systemonomic-mcp==0.1.1"
],
"env": {
"SYSTEMONOMIC_API_KEY": "<your systemonomic_api_key>"
}
}
}
}Environment variables
SYSTEMONOMIC_API_KEYsecret Your Systemonomic API key (generate at systemonomic.com/profile)
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
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-mcp2. Get an API Key
- Log in to Systemonomic
- Go to Profile → API Keys
- Click Generate API Key
- 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.pyFrequently asked questions
What is Systemonomic — Work Domain Analysis & AI Task Suitability?
Model work domains, score tasks for AI suitability, and design organisations.
How do I install Systemonomic — Work Domain Analysis & AI Task Suitability?
It runs on your machine. In Claude Code: claude mcp add systemonomic-work-domain-analysis-ai-tas -e 'SYSTEMONOMIC_API_KEY=<your systemonomic_api_key>' -- uvx systemonomic-mcp==0.1.1. For other clients, paste the JSON configuration from this page into their MCP settings.
Does Systemonomic — Work Domain Analysis & AI Task Suitability need an API key?
Yes. It expects SYSTEMONOMIC_API_KEY, which you set in its configuration.
Is Systemonomic — Work Domain Analysis & AI Task Suitability open source?
Its code is public on GitHub, but the repository does not declare a standard license.
Who maintains Systemonomic — Work Domain Analysis & AI Task Suitability?
It is published by TonyC23. AI.tn lists it but does not maintain or endorse it.
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