How do I install Cadlens?

Cadlens is a local plugin. Install it using npm package: @cadlens/mcp-server and add the generated configuration snippet to your AI app's MCP config file. Then restart your AI app.

Is Cadlens safe to use?

Cadlens scored 5.2/10 (moderate risk) in MCP Marketplace's automated security scan. It has 7 high or critical findings to review. It's listed, but review the security report on this page before installing.

What credentials does Cadlens need?

Cadlens requires the following credentials or environment variables: CADLENS_API_KEY, CADLENS_API_BASE, WEBHOOK_PUBLIC_URL. You can find setup instructions on the server detail page.

What AI apps work with Cadlens?

Cadlens uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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Cadlens MCP Server

by Cadlens Co

Developer ToolsModerate5.2MCP RegistryLocal

Free

Server data from the Official MCP Registry

Model Context Protocol server that wraps the CADLens REST API.

About

Model Context Protocol server that wraps the CADLens REST API.

Security Report

5.2

Moderate5.2Moderate Risk

This is a well-structured MCP server for parsing CAD files via the Cadlens API. Authentication is properly handled via environment variable (CADLENS_API_KEY), permissions are appropriate for its purpose (file I/O, network HTTP calls to a specific API), and code quality is solid with good input validation and error handling. No critical security issues were identified. Supply chain analysis found 10 known vulnerabilities in dependencies (2 critical, 5 high severity). Package verification found 1 issue.

7 files analyzed · 14 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

env_vars

Check that this permission is expected for this type of plugin.

File System Read

Reads files on your machine. Normal for tools that analyze or process local data.

HTTP Network Access

Connects to external APIs or services over the internet.

What You'll Need

Set these up before or after installing:

Your CADLens API keyRequired

Environment variable: CADLENS_API_KEY

API base URL (default: https://api.cadlens.co/v1)Optional

Environment variable: CADLENS_API_BASE

Public URL for webhook auto-registration (optional)Optional

Environment variable: WEBHOOK_PUBLIC_URL

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-cadlens-co-cadlens-mcp": {
      "env": {
        "CADLENS_API_KEY": "your-cadlens-api-key-here",
        "CADLENS_API_BASE": "your-cadlens-api-base-here",
        "WEBHOOK_PUBLIC_URL": "your-webhook-public-url-here"
      },
      "args": [
        "-y",
        "@cadlens/mcp-server"
      ],
      "command": "npx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

cadlens-mcp

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.

Install

Get an API key from the Cadlens dashboard first — keys start with cadl_ and are created in the dashboard for free.

Claude Desktop / Cursor / Windsurf

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 Code CLI

claude mcp add cadlens \
  --env CADLENS_API_KEY=cadl_xxx \
  -- npx -y @cadlens/mcp-server

Development (build from source)

npm install
npm run build

export CADLENS_API_KEY="cadl_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
node dist/index.js

Tools

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.

Configuration

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.

Webhook short-circuit (optional)

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"

Development

npm run typecheck
npm run lint
npm test
npm run smoke   # tools/list smoke test against built binary

Project-scoped Claude agents

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.

GitHub Topics

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

License

MIT

Reviews

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Cadlens MCP Server

About

Security Report

Findings (14)Action required

Permissions Required

What You'll Need

How to Install

Documentation

cadlens-mcp

Install

Claude Desktop / Cursor / Windsurf

Claude Code CLI

Development (build from source)

Tools

Configuration

Webhook short-circuit (optional)

Development

Project-scoped Claude agents

Links

GitHub Topics

License

Reviews

No reviews yet

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