laserbrain
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@laserbrainread the weather field state"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
laserfield
A living weather field that thinks — exposed to any AI through MCP.
Renamed 2026-07-24. This was
laserbrain, which collided with the recursion harness published on PyPI under that name — a different product that had held the same word.pip install laserbrainfetches that harness, not this. GitHub redirects the old repo URL andlaserbrain.pyremains as a shim, so existing clones and MCP configs keep working.
laserfield 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,laserfield_core.py,laserfield.py— the core field simulationatmosphere.py,climate.py,weather.py— the atmospheric layersholm.py— holographic language model (the field's voice)pixie.py— field sprite/agent layermodules/— 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 morepython_mcp_client.py,js_mcp_client.js— client examplesexamples/— taps and creative outputs (laser texture, field tap)data/— vocabulary and geometry assets
Related MCP server: MCP Weather Server
Quick start
pip install -r requirements.txt
python3 mcp_server.pyThen add to your MCP client config (e.g. Claude Code):
{
"mcpServers": {
"laserfield": {
"command": "python3",
"args": ["/path/to/laserfield/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.
The family
laserfield is the context — a world with its own clock that keeps moving whether or not anything reads it. It is one of four, and the names carry the roles:
laserfield | the context | where you are — this repo |
laserbrain | the tools | where you should be — a fixed reference for agents, |
lasermind | the protocols | what counts as true — the proof, the claims, the scorers |
laserbeast | the body | the embodied case, where distance is measured in metres |
The field gives position; the harness gives origin; displacement is the difference.
laserbrain.field.FieldGround grounds once against this daemon and measures how far the
world has moved since — context displacement, which is a different question from how much
of a task is left.
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Maintenance
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