CAD-Query MCP Server
A server for generating and verifying CAD models using the CAD-Query Python library.
CAD-Query MCP Server
A Model Context Protocol (MCP) server that provides CAD generation and verification tools for Claude Code. This server enables conversational 3D modeling by exposing CAD-Query functionality through MCP tools.
Features
verify_cad_query- Validates CAD-Query generated models against criteriagenerate_cad_query- (Stub implementation) Generates CAD-Query Python scripts from descriptions- CAD-Query Integration - Full CAD-Query support for parametric 3D modeling
- STL/STEP Export - Direct export to 3D printing and CAD formats
- Visual Feedback - SVG generation for model inspection
Installation
# Install dependencies
uv sync
# For development with CAD verification capabilities
uv sync --extra cad
# Test the server
uv run python tests/test_server.py
# Run with MCP Inspector (interactive testing)
uv run mcp dev server.py
Claude Desktop Configuration
Add this to your Claude Desktop configuration file:
macOS
Location: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows
Location: %APPDATA%/Claude/claude_desktop_config.json
Configuration
{
"mcpServers": {
"cadquery-server": {
"command": "python",
"args": ["/path/to/cadquery-mcp-server/server.py"],
"env": {}
}
}
}
MCP Tools
verify_cad_query
Validates a CAD-Query generated model against specified criteria.
Parameters:
file_path(string): Path to the CAD-Query Python fileverification_criteria(string): Description of what to verify
Example:
{
"file_path": "models/coffee_mug.py",
"verification_criteria": "coffee mug with handle, 10cm height, 8cm diameter"
}
Returns:
{
"status": "PASS" | "FAIL",
"message": "Description of result",
"file_path": "Path to verified file",
"criteria": "Verification criteria used",
"details": "Additional verification details"
}
generate_cad_query (Stub Implementation)
Generates CAD-Query Python scripts from natural language descriptions.
NOTE: Currently returns a stub response indicating the feature is not yet implemented.
Parameters:
description(string): Natural language description of the desired 3D modelparameters(string, optional): Specific dimensions or constraints
Example:
{
"description": "Create a coffee mug with a handle, 10cm tall and 8cm diameter",
"parameters": "height=100mm, diameter=80mm, handle_width=15mm"
}
Returns:
{
"status": "NOT_IMPLEMENTED",
"message": "CAD code generation is not yet implemented",
"description": "Input description",
"parameters": "Input parameters",
"details": "Additional information"
}
CAD-Query Script Requirements
All CAD-Query scripts must end with show_object(result):
import cadquery as cq
result = cq.Workplane("XY").box(10, 10, 10)
show_object(result) # Required for processing
Development
Testing
# Test server functionality
uv run python tests/test_server.py
# Interactive testing with MCP Inspector
uv run mcp dev server.py
# Run evaluations
uv run python evaluations/evaluate_verify.py
Extending the Server
The current verify_cad_query implementation is a basic validator. You can enhance it to:
- Parse and validate CAD-Query syntax
- Execute model generation and catch errors
- Analyze resulting geometry dimensions
- Check for specific features and constraints
- Generate detailed validation reports
Dev tools
# formatting
uvx rff format
# running the MCP server
npx @modelcontextprotocol/inspector \
uv \
--directory $(pwd) \
run \
server.py
संबंधित सर्वर
Alpha Vantage MCP Server
प्रायोजकAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
LLMKit
AI cost tracking MCP server with 11 tools for spend analytics, budget enforcement, and session costs across Claude Code, Cursor, and Cline.
Lustre MCP
Premium Flutter UI components for AI coding agents — 46 widgets, 3 themes, design tokens that make Claude Code and Cursor produce beautiful Flutter apps instead of generic Material defaults.
iOS MCP Server
An iOS mobile automation server using Appium and WebDriverAgent.
Prefect
Interact with the Prefect API for workflow orchestration and management.
AI Sessions
Searching and access your AI coding sessions from Claude Code, Gemini CLI, opencode, and OpenAI Codex.
MCPR
Expose R functions through the Model Context Protocol (MCP) for seamless integration with AI assistants.
Adaptive Graph of Thoughts
An intelligent scientific reasoning framework that uses graph structures and Neo4j to perform advanced reasoning via the Model Context Protocol (MCP).
MLflow Prompt Registry
Access prompt templates managed in an MLflow Prompt Registry. Requires a running MLflow server configured via the MLFLOW_TRACKING_URI environment variable.
Remote Weather MCP Server
A remote, authentication-free MCP server for weather data, deployable on Cloudflare Workers or run locally via npm.
Zeek-MCP
Integrates Zeek network analysis with conversational AI clients. Requires an external Zeek installation.