Wraps the CADLens REST API so Claude can parse CAD files (DWG, DXF, DGN, PDF) into structured JSON without installing AutoCAD. Exposes seven tools: upload local files or URLs, poll job status, fetch results in four detail modes (summary, entities by type, entities on layer, full JSON), refresh presigned image URLs, list recent jobs, and delete artifacts. Supports optional webhook short-circuiting to cut polling latency when you tunnel a public URL to the local receiver. You'll need a CADLens API key from their dashboard. Reach for this when you want Claude to reason over drawing entities, layers, and metadata in architecture, engineering, or construction workflows.
CADLENS_API_KEY*secretYour CADLens API key
CADLENS_API_BASEdefault: https://api.cadlens.co/v1API base URL (default: https://api.cadlens.co/v1)
WEBHOOK_PUBLIC_URLPublic URL for webhook auto-registration (optional)
A Model Context Protocol server that wraps the Cadlens CAD parsing API so MCP-aware LLM clients (Claude Desktop, Claude Code, Cursor, Zed, Windsurf) can parse CAD files (.dwg, .dxf, .dwf, .dwfx, .dgn V7, .pdf, max 100 MB) and reason over the extracted entity, layer, and metadata payloads.
Cadlens converts CAD drawings into structured JSON without requiring AutoCAD or any desktop software — learn more at cadlens.co.
Get an API key from the Cadlens dashboard first — keys start with cadl_ and are created in the dashboard for free.
Add to your MCP client config (e.g. ~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": {
"cadlens": {
"command": "npx",
"args": ["-y", "@cadlens/mcp-server"],
"env": {
"CADLENS_API_KEY": "cadl_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
}
}
}
}
claude mcp add cadlens \
--env CADLENS_API_KEY=cadl_xxx \
-- npx -y @cadlens/mcp-server
npm install
npm run build
export CADLENS_API_KEY="cadl_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
node dist/index.js
| Tool | What it does |
|---|---|
cadlens_parse_file | Upload a local CAD file, poll until parsed (5 min budget), return summary. |
cadlens_parse_url | Download a CAD file from a URL, then parse it like parse_file. |
cadlens_get_job | Cheap status check (PENDING / PROCESSING / COMPLETED / FAILED). |
cadlens_get_result | Fetch parsed content. mode: summary (default), entities_by_type, entities_on_layer, full. |
cadlens_refresh_image_url | Re-fetch the 1h presigned PNG URL without re-downloading the full result. |
cadlens_list_jobs | The 100 most recent jobs for the configured API key. |
cadlens_delete_job | Delete a job and its S3 artifacts. Irreversible. |
| Env var | Required | Default | Notes |
|---|---|---|---|
CADLENS_API_KEY | yes | — | Created in the CADLens dashboard. |
CADLENS_API_BASE | no | https://api.cadlens.co/v1 | Set to http://localhost:3001/v1 for local dev. |
WEBHOOK_PORT | no | 0 (random) | Port for the in-process webhook receiver. |
WEBHOOK_PUBLIC_URL | no | unset | Set to a tunnel URL (ngrok/cloudflared) to let CADLens hit the local receiver. When set, parse calls auto-register the webhook and the poller short-circuits on receipt. |
REQUEST_TIMEOUT_MS | no | 30000 | Per-HTTP-request timeout for CADLens calls. |
If WEBHOOK_PUBLIC_URL is set, parse_file / parse_url register a per-process webhook URL alongside the upload. The webhook handler updates an in-memory job-state cache; the poller checks that cache before each HTTP GET and returns early when COMPLETED / FAILED arrives. This trims worst-case latency by up to one full poll tick (~1 s) without changing the tool surface.
Example tunnel setup:
cloudflared tunnel --url http://localhost:8787 &
export WEBHOOK_PORT=8787
export WEBHOOK_PUBLIC_URL="https://<your-tunnel>.trycloudflare.com"
npm run typecheck
npm run lint
npm test
npm run smoke # tools/list smoke test against built binary
This repo ships five agents under .claude/agents/:
cadlens-api-debugger — diagnoses unexplained CADLens 4xx/5xx using mcp-server-reference.md.mcp-tool-tester — drives JSON-RPC against the built server to validate tool responses.mcp-tool-implementer — scaffolds new tools following the existing src/tools/* pattern.cad-drawing-summarizer — uses the MCP tools to summarize a CAD file in natural language.cad-layer-inspector — drills into a single layer of a parsed drawing.Add these topics to this repo for discovery:
mcp mcp-server model-context-protocol ai-agents claude cad dwg dxf cad-api llm-tools engineering-api
MIT