Decisio Server

Structured decision-making for AI assistants — powered by the Analytic Hierarchy Process (AHP), the same framework trusted by NASA, Boeing, and the World Bank.

When someone asks an AI "help me choose between job offers" or "which city should I move to", the AI can use Decisio's MCP tools to run a mathematically rigorous analysis instead of just listing pros and cons.

Tools

Tool	Description
decisio_list_templates	Browse built-in templates (career, business, technology, etc.)
decisio_create_decision	Start a new AHP analysis with criteria and options
decisio_compare	Set pairwise comparisons (Saaty 1-9 scale)
decisio_calculate	Run AHP calculation — get ranked results with scores
decisio_devils_advocate	Challenge the winning option
decisio_quick_decide	All-in-one: define + compare + calculate in a single call

Quick Start

Install

npm install -g decisio-mcp-server

Configure in Claude Desktop / VS Code / Cursor

Add to your MCP config:

{
  "mcpServers": {
    "decisio": {
      "command": "npx",
      "args": ["-y", "decisio-mcp-server"]
    }
  }
}

Build from source

git clone https://github.com/decisio-app/decisio-mcp-server.git
cd decisio-mcp-server
npm install
npm run build

Example Conversation

User: Help me choose between Berlin, Lisbon, and Austin for relocation.

AI (uses decisio_create_decision with relocation template):

Created decision with criteria: Cost of Living, Career Opportunities, Quality of Life, Weather & Climate, Social & Community.

AI (walks through pairwise comparisons):

Which matters more to you: Cost of Living or Career Opportunities?

User: Career, definitely — about 5x more important.

AI (uses decisio_compare):

Got it. How about Career vs Quality of Life?

(... continues through all pairs ...)

AI (uses decisio_calculate):

Results (AHP Analysis)

1. Lisbon — 38.2%
2. Austin — 32.1%
3. Berlin — 29.7%

Consistency Ratio: 0.04 (Very High confidence)

AI (uses decisio_devils_advocate):

The gap between Lisbon and Austin is only 6.1pp. If Career Opportunities weighted less, Austin could overtake...

How AHP Works

1. Define your goal, criteria, and options
2. Compare criteria pairwise: "Is Cost more important than Quality? By how much?"
3. Compare options under each criterion: "For Cost, is Berlin better than Lisbon?"
4. Calculate — AHP computes weighted scores using eigenvector mathematics
5. Validate — Consistency Ratio checks if your comparisons are logically coherent

The Saaty scale (1-9) quantifies preferences:

Value	Meaning
1	Equal importance
3	Moderate importance
5	Strong importance
7	Very strong importance
9	Extreme importance
2,4,6,8	Intermediate values
1/3, 1/5, etc.	Inverse (B preferred over A)

Full Experience

For Playbook, Outcome Tracking, PDF Export, and the full AI-powered Devil's Advocate — download Decisio on iOS:

Download on App Store

License

MIT