Systemonomic — Work Domain Analysis & AI Task Suitability MCP server

by TonyC23·io.github.TonyC23/systemonomic-mcp·v0.1.2

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

B72/100grade B

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B72/100

full report

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Systemonomic — Work Domain Analysis & AI Task Suitability tools (34, 9 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

accept_suggestions
Accept task suggestions, promoting them to actual project tasks.
apply_proposal
Apply an AI-generated restructure proposal to the project.
create_org_snapshotwrite action
Create a snapshot of the current org design for version control.
create_projectwrite action
Create a new project.
create_taskwrite action
Create a new task in a project.
create_wda_linkwrite action
Create a means-ends link between two WDA nodes.
create_wda_nodewrite action
Create a new WDA node at a specific level.
delete_wda_linkwrite action
Delete a means-ends link between two WDA nodes.
delete_wda_nodewrite action
Delete a WDA node and all its connected links.
derive_task_suggestions
Use AI to derive detailed task suggestions from WDA objects.
export_org_design_json
Export the org design as a JSON document.
export_project
Export a complete project (WDA, tasks, ATSS, org design) as JSON.
generate_pdf_report
Generate a comprehensive PDF report for a project.
generate_tasks_from_wda
Auto-generate tasks from the WDA Objects level.
generate_wda
Generate a complete WDA from a text description using AI.
get_atss_results
Get stored ATSS results for a project.
get_org_design
Get the current organizational design for a project.
get_project_state
Get the complete state of a project: WDA nodes, links, tasks, ATSS results, and org design.
get_project_stats
Get summary statistics for a project: node counts by level, task count, ATSS completion, etc.
get_report_status
Check the readiness status of a project's report.
import_wda
Import WDA nodes and links into an existing project.
list_atss_runs
List all ATSS assessment runs for a project, with timestamps and summaries.
list_org_snapshots
List all org design snapshots for a project.
list_projects
List all projects owned by the authenticated user.
list_suggestions
List all pending task suggestions for a project.
list_tasks
List all tasks in a project.
list_wda_links
List all means-ends links in a project's WDA.
list_wda_nodes
List all WDA nodes in a project.
persist_atss_results
Persist ATSS assessment results to the project.
persist_org_design
Save an organizational design to a project.
propose_restructure
Generate an AI-powered restructure proposal from ATSS results.
run_atss_batchwrite action
Run ATSS (Automated Task Suitability Scoring) on all tasks in a project.
update_wda_nodewrite action
Update an existing WDA node's label, level, or description.
validate_raci
Validate the RACI matrix for a project.

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

no findings

Code scan7 source files scanned25/25
–Live reliabilityno gateway calls yet and no remote to proben/a
–Tool poisoningtools not inspected (local package is not executed); not countedn/a
Auth qualitystatic API keys via environment variables6/15
Maintenancelast push 168 days ago8/15
Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10

Overall 72/100. Components that don't apply are left out of the denominator. Any critical finding is an F.Rubric Appeal a finding JSON

How Systemonomic — Work Domain Analysis & AI Task Suitability compares

Against every graded Productivity MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score: 72/100; higher than 33% of 1,299 Productivity servers
Tools: 34; the typical Productivity server has 7
Tools that change things: 26%; typical: 0%. Fewer write tools means less an agent can break
Downloads a week: 22; more than 7% of 427 Productivity servers with a package

What its tools let an agent do: 20 read · 9 create · 1 change · 2 delete · 2 run or deploy

Install Systemonomic — Work Domain Analysis & AI Task Suitability in Claude Code, Cursor or VS Code

claude mcp add systemonomic-mcp -- uvx systemonomic-mcp

Add to Cursor

What the publisher says

From the Systemonomic — Work Domain Analysis & AI Task Suitability repository's README, as published. We do not edit it. Read it 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-mcp

2. Get an API Key

Log in to Systemonomic
Go to Profile → API Keys
Click Generate API Key
Copy the key (starts with sksys) — 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 claudedesktopconfig.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 systemonomicmcp.wdaserver
Environment: SYSTEMONOMICAPIKEY=sksys...

Repeat for atssserver and orgserver.

Available Servers

systemonomic-wda — Work Domain Analysis

systemonomic-atss — Assessment & Tasks

systemonomic-org — Organizational Design

Example Conversations

"Help me model our procurement process"

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Systemonomic — Work Domain Analysis & AI Task Suitability: common questions

Is Systemonomic — Work Domain Analysis & AI Task Suitability MCP server safe?: Mostly: it is graded B (72/100). Read the Systemonomic — Work Domain Analysis & AI Task Suitability safety report
How do I install Systemonomic — Work Domain Analysis & AI Task Suitability?: It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Systemonomic — Work Domain Analysis & AI Task Suitability need an API key?: Yes. The registry entry asks for SYSTEMONOMIC_API_KEY.
Is Systemonomic — Work Domain Analysis & AI Task Suitability maintained?: The last commit was 205 days ago (2026-04-13). The latest release is v0.1.2.
What can I use instead of Systemonomic — Work Domain Analysis & AI Task Suitability?: Servers from other publishers that do the same job: CLEO MCP Server, Google Calendar MCP server and Obsidian Vault MCP server.
How does Systemonomic — Work Domain Analysis & AI Task Suitability compare with other Productivity MCP servers?: safety score 72/100 (higher than 33% of 1,299 Productivity servers); tools 34 (the typical Productivity server has 7); tools that change things 26% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

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