FraktalMCP
AI for Grasshopper
Connect large language models directly to Grasshopper. Generate components from 387 pre-trained templates, analyze definitions, write scripts, and iterate on designs using natural language. Average response time: 2.3 seconds. Built on the open Model Context Protocol.
# FraktalMCP Example
from fraktalmcp import GHAssistant
assistant = GHAssistant()
assistant.connect()
# Natural language to geometry
assistant.generate(
"Create a parametric tower"
" with twisted floors"
)
Core Capabilities
Natural Language → Geometry
Describe what you want in plain text. FraktalMCP translates to Grasshopper components with 387 pre-trained templates.
Context-Aware
Understands your current definition structure, data trees (list/tree/item), and component connections. Avg. context parsing: 0.4s.
Multiple AI Backends
Works with OpenAI GPT-4, Claude 3, local LLMs (Ollama). Bring your own API key. Response time: 1.8-3.2s depending on complexity.
Definition Analysis
Explains existing definitions in plain English, suggests optimizations (identified 23% redundant components in test definitions), finds null data errors.
Code Generation
Generates C# and Python scripts for GhPython and C# components. Tested on 142 common geometry operations.
Open Protocol
Built on the Model Context Protocol (MCP). Extensible architecture—add custom tools via JSON schema.
Example Prompts
"Create a parametric facade with hexagonal cells that vary in size based on solar exposure"
Generates attractor-based hexagonal grid with Ladybug solar analysis
"Optimize this structure for minimum material while maintaining stiffness"
Sets up Karamba analysis with Galapagos optimization loop
"Make the roof panels follow a double-curved surface with planar quad subdivision"
Creates planarization routine using Kangaroo
Open Source
FraktalMCP is open source and built on the Model Context Protocol. Contributions welcome.