Server data from the Official MCP Registry
Model work domains, score tasks for AI suitability, and design organisations.
About
Model work domains, score tasks for AI suitability, and design organisations.
Security Report
Valid MCP server (1 strong, 10 medium validity signals). 3 known CVEs in dependencies (0 critical, 3 high severity) ⚠️ Package registry links to a different repository than scanned source. Imported from the Official MCP Registry.
7 files analyzed · 4 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
What You'll Need
Set these up before or after installing:
Environment variable: SYSTEMONOMIC_API_KEY
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-tonyc23-systemonomic-mcp": {
"env": {
"SYSTEMONOMIC_API_KEY": "your-systemonomic-api-key-here"
},
"args": [
"systemonomic-mcp"
],
"command": "uvx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
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
- 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.py
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