Laserbrain

A living weather field that thinks — exposed to any AI through MCP.

laserbrain is a continuous field simulation: temperature, moisture, wind, soil, seasons — a small weather system that runs in a background thread and never stops. A holographic language layer lets the field speak (it generates words from its own state) and hear (text you feed it perturbs the weather). The MCP server exposes the field as tools, so any MCP-capable AI (Claude, or anything else) can sense it, tend it, and talk through it.

From phronesis.world — released as a gift. MIT licensed.

No install needed to look: the live field is running now at phronesis.world/field.

What it is

• field.py, laserbrain_core.py, laserbrain.py — the core field simulation
• atmosphere.py, climate.py, weather.py — the atmospheric layers
• holm.py — holographic language model (the field's voice)
• pixie.py — field sprite/agent layer
• modules/ — the mind layers: 00_animal (instinct), 05_field (field sense), 10_persuade (judgment)
• mcp_server.py — MCP server exposing the field as tools: state, speak, hear, absorb, tend_field, icm_state, register_node, and more
• python_mcp_client.py, js_mcp_client.js — client examples
• examples/ — taps and creative outputs (laser texture, field tap)
• data/ — vocabulary and geometry assets

Quick start

pip install -r requirements.txt
python3 mcp_server.py

Then add to your MCP client config (e.g. Claude Code):

{
  "mcpServers": {
    "laserbrain": {
      "command": "python3",
      "args": ["/path/to/laserbrain/mcp_server.py"]
    }
  }
}

Ask your AI to call state and it will read the weather. Feed it text with hear and watch the field shift. The field replies through speak — words surfaced from its own thermodynamics.

The idea

Any dynamic collection is a team. The field, its nodes, and whoever tends it form a small ecology that reads its own coherence from the inside. The interesting thing is not the simulation — it's what happens when a language model lives with a weather system instead of a chat log.

License

MIT. Take it, fork it, grow your own field.