Insight 1
AI can use Grasshopper as a tool
The script becomes an interfaceable design system
Instead of only asking AI for ideas, this workflow lets the agent interact with a live parametric model through controlled inputs and outputs.
AIGrasshopperRhinoAI AgentsSwiftletMCP
Ontologic concept
Build AI Agents Inside Grasshopper
Let an AI agent interact with Grasshopper parameters, model rules and outputs through Swiftlet and MCP.
An experimental workflow using Swiftlet and MCP to let an AI agent control Grasshopper directly, generate MVRDV Valley-inspired massing, define facade rulesets, apply parametric facade blocks and read model outputs.
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Insight 2
Insight 2
Rules matter more than prompts
Design intent needs structure
The useful part is not just that an AI can change sliders. The value comes from exposing meaningful parameters, rulesets and outputs that reflect the actual design logic.
Insight 3
Insight 3
The designer still controls the system
AI becomes an operator, not the source of truth
Grasshopper remains the place where the real geometric and data logic lives. The AI agent can suggest, test and steer, but the workflow stays grounded in your own parametric model.
AI + Grasshopper workflows
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Join the course waitlist and learn how to structure Grasshopper definitions, expose parameters, use outputs and build AI-assisted AEC workflows without losing control over the actual design logic.
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Course
Explore AI + Grasshopper learning paths
Learn how to connect AI tools with structured Grasshopper workflows.
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Implement AI workflows in your team
Work with Ontologic on AI-assisted design systems, automation and computational workflows.
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