# SolidWorks MCP Bridge

> SolidWorks MCP Bridge — said-aer-solidworks-mcp-bridge. Use this tool when you need to integrate local large language models (LLMs) with SolidWorks for read-only inspection and analysis of 3D models, enabling access to features, dimensions, and mass properties. It solves problems related to design inspection, data extraction, and file export, providing a bridge between LLMs and SolidWorks via its COM API. Ideal for use cases requiring automated design analysis and data retrieval, with plans for future expansion to editing and generation capabilities.

Canonical page: https://skillsregistry.net/skills/said-aer-solidworks-mcp-bridge  
JSON: https://api.skillsregistry.net/v1/skills/said-aer-solidworks-mcp-bridge

## Description

MCP server that integrates local LLMs (via Ollama) with SolidWorks through its COM API, enabling read-only inspection of features, dimensions, equations, mass properties, and file exports. It supports models like Qwen3 and plans future expansion to editing and generation.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/i70sud3jr4)
- **Repository:** <https://github.com/Said-AER/solidworks-mcp-bridge>

## 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": "said-aer-solidworks-mcp-bridge"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/said-aer-solidworks-mcp-bridge` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/said-aer-solidworks-mcp-bridge/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
