1. Conduid
  2. AI
  3. onshape
MCP server · AI

onshape

mcp server for interacting with onshape

Unclaimed devtools
52Fair

Scored 19 days ago · breakdown

About onshape

onshape is an MCP server published by git+altendky in the AI category: mcp server for interacting with onshape. It has been installed 0 times through Conduid.

Install

Install
npx onshape-mcp
Claude Code
claude mcp add onshape-mcp -- npx -y onshape-mcp
npx
npx -y onshape-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Ask AI

Ask AI about onshape

Powered by Claude · Grounded in docs

I know everything about onshape. Ask me about installation, configuration, usage, or troubleshooting.

Security checks

  • ·README presentNot checked yet.
  • ·License declaredNot checked yet.
  • ·Tests presentNot checked yet.
  • ·Dependencies pinnedNot checked yet.
  • ·No dynamic code executionNot checked yet.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

README

Onshape MCP

AI-assisted access to your Onshape CAD documents.

What This Is

Onshape MCP connects your AI assistant to Onshape. You describe what you want in Onshape terms — create a sketch, extrude a part, export an STL — and the AI handles the API calls. This is a helper for people who already know Onshape, not a replacement for CAD skills.

Status

Early development. This is offered for people to try if they're interested — things may not always work as expected, and feedback is appreciated.

Access to the hosted servers is currently limited to a closed testing group. Don't call us, we'll call you.

Getting Started

Local Setup (Claude Desktop, OpenCode, or any MCP client)

This is the recommended path. A local server can read and write files on your machine directly — screenshots, exports, and FeatureScript — instead of passing content through the conversation.

Step 1: Get the server binary

Pick whichever is easier for you:

  • npx (requires Node.js): No separate install needed — your MCP client runs npx --yes onshape-mcp and it downloads automatically.
  • Pre-built binary: Download from GitHub Releases and save it somewhere convenient.

Step 2: Configure your MCP client

Tell your MCP client how to launch the server.

Claude Desktop

Add to your Claude Desktop config (claude_desktop_config.json):

Using npx:

{
  "mcpServers": {
    "onshape": {
      "command": "npx",
      "args": ["--yes", "onshape-mcp"]
    }
  }
}

Using the downloaded binary:

{
  "mcpServers": {
    "onshape": {
      "command": "/path/to/onshape-mcp"
    }
  }
}

OpenCode

Add to your opencode.json:

Using npx:

{
  "mcp": {
    "onshape": {
      "type": "local",
      "command": ["npx", "--yes", "onshape-mcp"]
    }
  }
}

Using the downloaded binary:

{
  "mcp": {
    "onshape": {
      "type": "local",
      "command": ["/path/to/onshape-mcp"]
    }
  }
}

Other MCP clients

Any MCP client that supports stdio transport can launch this server. The command is either npx --yes onshape-mcp or the path to the downloaded binary.

Step 3: Try it

Ask your AI assistant to create a new Onshape document with a simple shape. If you haven't authenticated yet, it will give you a URL to open in your browser to log into Onshape and approve access.

Web Setup (Claude.ai or other web MCP clients)

No local installation needed. Add https://onshape.mcp.fstab.net/mcp as a remote MCP server in your client's settings. You'll be prompted to log into Onshape when you first use it.

The web transport has no access to your local filesystem. FeatureScript and other file content passes through the conversation instead of being read from and written to disk, which uses significantly more tokens.

Tips

  • Share document URLs. Paste an Onshape document URL into the conversation to give the AI context about what you're working with.
  • Use Onshape vocabulary. Say "extrude," "fillet," "sketch on the top face," etc. The AI has built-in knowledge about Onshape operations.
  • Multiple steps are normal. The AI discovers API endpoints dynamically, so a single request may involve several steps behind the scenes.
  • Be specific when things go wrong. If the AI takes a wrong turn, try describing the Onshape operation more precisely.

What You Can Do

  • Browse and explore your Onshape documents
  • Create new documents and parts
  • Build features: sketches, extrudes, revolves, sweeps, fillets, construction planes
  • Take screenshots of Part Studios from different angles
  • Export parts (STL, STEP, and other formats)
  • Work with FeatureScript — write custom features and debug existing ones

The AI has access to the full Onshape REST API, so anything available through the API is potentially reachable. Results will vary — some operations work more reliably than others at this stage.

Supported Platforms

Platform Architecture
Linux x86_64, aarch64
macOS x86_64, aarch64 (Apple Silicon)
Windows x86_64

Project Documentation

For development, architecture, and contribution details, see docs/src/project/.

License

Licensed under either of:

at your option.

README mirrored from the source repository 19 days ago. The original is authoritative.

Questions

About onshape

How do I install onshape?

Run npx onshape-mcp, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is onshape safe to use with an AI agent?

Its trust score is 52 out of 100 (fair). It passes 0 of 1 static security checks; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is onshape still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.