MindFry

A Subjective Biological Memory Substrate

"Databases store data. MindFry feels it."

⚠️ EXPERIMENTAL: MindFry is currently in active R&D. The API is volatile. It simulates biological memory processes which may result in data inhibition (data loss from the user's perspective) based on the system's "mood". Do not use for banking.

What Makes This Different?

Traditional databases are objective — they store exactly what you give them, forever (or until you delete it).

MindFry is subjective — it processes data through a simulated cognitive layer that can:

• Forget data that isn't accessed (organic decay)
• Suppress data it finds antagonistic (mood-based inhibition)
• Strengthen frequently accessed data (Hebbian learning)
• Propagate stimulation through neural bonds (synaptic chains)

Core Principles

Tri-Cortex Architecture

Decisions are made using Balanced Ternary Logic (Setun):

• +1 = True / Excitation
• 0 = Unknown / Neutral
• -1 = False / Inhibition

The database has a Personality Octet (8 dimensions) and a Mood that affects data prioritization.

Mood & Personality

Note: Mood affects which data surfaces first, not whether your requests succeed. All data remains accessible — mood just influences the "attention" priority.

Mood modulates the consciousness threshold:

• High Mood → More memories feel "close" and accessible
• Low Mood → Only the most important memories surface naturally

Override anytime: Use BYPASS_FILTERS flag for guaranteed access regardless of mood.

Synaptic Propagation

When you stimulate("A"):

A (+1.0) → B (+0.5) → C (+0.25) → ... (damped)

Touch one memory, its neighbors tremble.

Resurrection

Shutdown and restart. The database remembers:

• Its mood
• Its personality
• All lineages and bonds

Quick Start

Docker (Recommended)

docker run -d -p 9527:9527 ghcr.io/cluster-127/mindfry:latest

From Source

# Clone
git clone https://github.com/cluster-127/mindfry.git
cd mindfry

# Run server
cargo run --release --bin mindfry-server

# In another terminal
cargo run --bin mfcli -- ping
cargo run --bin mfcli -- create fire 0.9
cargo run --bin mfcli -- stimulate fire 1.0
cargo run --bin mfcli -- stats

SDK

npm install mindfry

import { MindFry } from 'mindfry'

const brain = new MindFry({ host: 'localhost', port: 9527 })
await brain.connect()

// Touch one memory...
await brain.lineage.stimulate({ key: 'trauma', delta: 1.0 })

// ...and its neighbors tremble
const associated = await brain.lineage.get('fear')
console.log(associated.energy) // Increased by propagation

Status

License

Apache-2.0 © Erdem Arslan

"If you're not embarrassed by the first version of your product, you've launched too late." — Reid Hoffman