# Grasshopper Parametric Design

> Use this tool when you need to integrate AI assistance into your parametric design workflow, enabling natural language commands to create and manipulate designs in Grasshopper. It solves problems of inefficient design iteration and limited accessibility to parametric modeling for non-experts, providing a bidirectional communication system between Grasshopper and Claude Desktop. The tool accepts natural language inputs and outputs parametric designs, ideal for architects, designers, and engineers seeking to streamline their design processes.

Canonical page: https://skillsregistry.net/skills/alfredatnycu-grasshopper-parametric-design  
JSON: https://api.skillsregistry.net/v1/skills/alfredatnycu-grasshopper-parametric-design

## Description

Grasshopper MCP Bridge connects Grasshopper (a visual programming environment for Rhino) with Claude Desktop through a bidirectional communication system. Developed by alfredatnycu, it consists of a Grasshopper plugin component (GH_MCP.gha) that provides a TCP server and a Python bridge server that implements the Model Context Protocol. The system includes a component knowledge base with information about common Grasshopper components, their parameters, and connection rules, enabling Claude to create and manipulate parametric designs through natural language commands. This implementation is particularly valuable for architects, designers, and engineers who want to leverage AI assistance for parametric modeling workflows without leaving their conversation interface.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/alfredatnycu-grasshopper-parametric-design)
- **Repository:** <https://github.com/alfredatnycu/grasshopper-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "alfredatnycu-grasshopper-parametric-design"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alfredatnycu-grasshopper-parametric-design` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alfredatnycu-grasshopper-parametric-design/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt