Systemonomic — Work Domain Analysis & AI Task Suitability

Model work domains, score tasks for AI suitability, and design organisations.

Open source Open in the app JSON README (API)

About

Model work domains, score tasks for AI suitability, and design organisations.

Details

Kind: MCP servers
Topic: No topic detected
Publisher: tonyc23
Origin: official
Category: ferramentas
Transport: local
Version: 0.1.2
Last push: 2026-04-13T09:51:56Z
Repository state: ativo
Language: Python
License: NOASSERTION
Added: 2026-08-29 03:02:17
Updated: 2026-08-29 03:02:17
Origin id: io.github.TonyC23/systemonomic-mcp

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

```bash
pip install systemonomic-mcp
```

### 2. Get an API Key

1. Log in to [Systemonomic](https://systemonomic.com)
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:

```bash
export SYSTEMONOMIC_API_KEY="sk_sys_your_key_here"
```

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

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

### 4. Add to Claude Desktop

Add to your `claude_desktop_config.json`:

```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

```bash
# 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
```

Systemonomic — Work Domain Analysis & AI Task Suitability

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