Hardware MCP Server
Click on "Deploy 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., "@Hardware MCP Serverdesign a heatsink for a 50W CPU and simulate its thermal performance"
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.
Hardware for MCP
This repository shows examples of how you can use a language model to perform tool calls for:
building a CAD part
running heat transfer simulations
This repository uses the Model Context Protocol (MCP)
Install Dependencies
First, clone the current GitHub repository with the following command.
git clone https://github.com/TheFloatingString/mcp-for-hardware.git
cd mcp-for-hardwareNow, install all the Python dependencies using the uv package manager:
pip install uv
uv syncInstall ngrok or any similar tunelling services. ngrok can be installed from https://ngrok.com/downloads
Next, if you use ngrok, run:
ngrok http 8000This will expose port 8000 (which we will be using soon for the MCP server) to a specific URL.
You should see a publicly visible URL after running the ngrok command. Keep note of this, you will need to add this in the .env file's environment variables.
Configure Environment Variables
Create a .env file and add the following environment variables
SERVER_BASE_URL=""
ANTHROPIC_API_KEY=""Quickstart
In one terminal, run the MCP server with the following:
uv run server.pyIn a second terminal, run the client with the following:
uv run client.pyThis server cannot be deployed
Maintenance
Related MCP Connectors
- OwlCADOAuthcom.owlcad
Parametric 3D CAD for AI agents: build print-ready parts, check them, export STL, 3MF or STEP.
CAD in ChatGPT and Claude: editable parts, STEP/STL/drawings, in-chat 3D, automatic checks.
AI-callable calculators and engineering models with real formulas. No hallucinated math.
Run FDS, OpenFOAM, CalculiX and other engineering simulations on cloudHPC from your AI assistant.
Related MCP Servers
- AlicenseNot gradedqualityAmaintenanceEnables coding agents to convert natural language engineering prompts into editable parametric CAD models with deterministic parsing, validation, and edit support.5Apache 2.0
- FlicenseNot gradedqualityBmaintenanceEnables agent-assisted CAD engineering, allowing users to create, validate, and export CAD designs through natural language, with a deterministic engine that has zero LLM runtime dependency.-
- AlicenseAqualityAmaintenanceEnables LLM agents (and humans at a terminal) to drive FreeCAD through 280+ structured tools for parametric mechanical design, drawings, FEM/CFD and other simulations, and manufacturing checks. Also supports multi-agent orchestration, letting a team of agents split one product into components, build them in parallel, and merge them back together with fitting joints.28645 PyPI13Apache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables AI assistants to build and edit native CAD parts and assemblies, inspect saved geometry and measurements, retain revisions, run mechanism and interference checks, and export STEP/STL/GLB artifacts through MCP tools.MIT