For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
  • Workflows
    • Overview
  • Get Started
    • MCP Quick Start
    • API Quick Start
  • MCP Server
    • Overview
    • Installation
  • Direct API
    • Overview
    • Authentication
    • Error Handling
  • Core Concepts
    • Minds, Snapshots, & Simulations
    • SOC 2, HIPAA, & GDPR
LogoLogo
LogoLogo
On this page
  • Minds
  • What it does
  • Real-world example
  • Available operations
  • Using minds with Claude
  • Snapshots
  • Training process
  • Data requirements
  • Available operations
  • Training with Claude
  • Simulations
  • How to write effective scenarios
  • What you get back
  • Available operations
  • Simulating with Claude
  • Quick Start
  • What’s Next?
Core Concepts

Core Concepts

Understand the fundamental building blocks of Mind Reasoner.
Was this page helpful?
Previous
Built with

Mind Reasoner MCP

Mind Reasoner has three core concepts: Minds, Snapshots, and Simulations. Master these, and everything else becomes intuitive.

The basics: Create a Mind → Upload transcripts → Run Simulations


Minds

A mind is a container that represents a person. Think of it as a digital profile.

Overview
Example
API Actions
MCP Tools

What it does

  • Stores conversation transcripts — Upload and manage training data
  • Holds metadata — Name, creation date, and configuration
  • Creates snapshots — Generate multiple AI models over time as data evolves

Minds are the foundation of Mind Reasoner. Each mind represents one person and can have unlimited snapshots trained from different datasets or time periods.


Snapshots

A snapshot is a trained AI model built from conversation transcripts. It captures how someone thinks and communicates at a specific point in time.

How It Works
Requirements
API Actions
MCP Tools

Training process

1

Upload Data

Provide conversation transcripts (.vtt, .pdf, or .docx). Minimum: 10-20 conversations or 5,000+ words.

2

AI Training

Mind Reasoner analyzes across hundreds of dimensions of psychometrics. Takes 5-15 minutes.

3

Ready to Use

Once complete, run unlimited simulations without re-training.

More data = better accuracy. Use recent transcripts (last 6 months) for best results.


Simulations

A simulation predicts how someone would respond to any scenario based on their trained snapshot.

Writing Scenarios
Response Details
API Actions
MCP Tools

How to write effective scenarios

Be Specific

Vague: “How would they handle a complaint?”

Specific: “A customer received a damaged product 3 days before their event. They need a replacement by tomorrow, but the product is out of stock. How would you respond?”

Include Context
  • Emotional state — frustrated, confused, urgent
  • Time constraints — by tomorrow, within 24 hours
  • Constraints — out of stock, over budget
  • Desired outcome — resolution, information
Add Relevant Details
  • Background information
  • Stakeholder concerns
  • Business constraints
  • Historical context

Quick Start

Choose how you want to get started:

MCP Server

Use Claude to create minds with natural language. No code required.

Direct API

Build custom applications with HTTP REST API. Full programmatic control.


What’s Next?

Explore Workflows

See how organizations integrate Mind Reasoner into business processes

MCP Quick Start

Connect Claude in 5 minutes

API Guide

Build with the Direct API