Agent native · Model Context Protocol

Give your AI agent CAD vision.

CADLens ships a Model Context Protocol server. Point Claude — or any MCP client — at it, and the agent can parse a DWG, DXF, or DWF drawing, walk its layers, count entities, measure geometry, and pull a preview image on its own. Seven tools, your existing API key, no glue code.

Get an API key · Free 50/mo →MCP docs
01CONNECT

One command. No install.

The hosted server speaks Streamable HTTP and authenticates with the same cadl_ key you already use for REST. Add it to Claude Code:

claude mcp add --transport http cadlens \
  https://api.cadlens.co/mcp \
  --header "Authorization: Bearer cadl_your_key_here"

Or drop it into Claude Desktop's config, running locally over stdio:

{
  "mcpServers": {
    "cadlens": {
      "command": "npx",
      "args": ["-y", "cadlens-mcp"],
      "env": { "CADLENS_API_KEY": "cadl_your_key_here" }
    }
  }
}

Then just ask: “Parse this floor plan and tell me how many circles are on the ELECTRICAL layer.”

02THE TOOLS

Seven tools the agent actually needs.

Each one wraps the same REST endpoint documented in our API reference, with identical authentication, ownership checks, and plan quotas.

  • parse_cad_file Upload a DWG, DXF, or DWF file and parse it. Waits for the result by default.
  • get_job_status Check whether a parse is pending, processing, complete, or failed.
  • get_job_result Read the vector JSON — summary first, then drill into a layer or entity type.
  • get_job_image Get pre-signed PNG preview URLs, one per sheet.
  • list_jobs List recent jobs on the account, newest first.
  • delete_job Delete a job and its artifacts.
  • get_usage Plan, quota, requests used, and remaining for the current period.
03CONTEXT BUDGET

Built for a context window.

A single drawing can carry tens of thousands of entities. Dumping that into a model is expensive and usually useless, so get_job_result is progressive by default:

  • summary (default) — file info, per-sheet and per-layer counts, layer names and colours, bounding boxes. No geometry.
  • entities_on_layer / entities_by_type — a filtered slice, capped at 500 entities, with an honest truncated flag when there is more.
  • full — everything, when the agent really does need everything.

The agent looks before it leaps: read the summary, pick the layer that matters, pull only those entities.

04DISCOVERY

Readable by machines.

An agent that has never heard of CADLens can find its way in without a human. Everything below is public, unauthenticated, and cacheable:

  • /.well-known/mcp/server-card.json — both transports, the auth scheme, every tool.
  • /.well-known/agent-skills/index.json — SKILL.md manifests with SHA-256 digests.
  • /.well-known/api-catalog — RFC 9727 linkset to docs, OpenAPI, and Postman.
  • /llms.txt and /llms-full.txt — plain-text context, no markup to strip.
  • Accept: text/markdown — pages return markdown instead of HTML.
  • WebMCP — browser agents get in-page tools on navigator.modelContext to search these docs and navigate the site.
05 — FAQ

MCP questions.

It is a Model Context Protocol server that exposes CAD parsing as tools an AI agent can call directly. Connect Claude Code, Claude Desktop, or any MCP client, and the agent can upload a DWG, DXF, or DWF file, read its layers and entities, and fetch a preview image without you writing any integration code.

Run: claude mcp add --transport http cadlens https://api.cadlens.co/mcp --header "Authorization: Bearer cadl_your_key". That is the hosted server, so there is nothing to install. For Claude Desktop, add a cadlens entry to the mcpServers block in claude_desktop_config.json using npx -y cadlens-mcp with CADLENS_API_KEY set.

No. The MCP server uses the same CADLens API key as the REST API, sent as Authorization: Bearer. We recommend issuing a dedicated key for agent use so it can be revoked independently.

No. An MCP parse counts as one parse against your monthly plan quota, exactly like a POST /v1/parse call. Failed jobs are never billed.

No. get_job_result defaults to a summary — file info, sheet and layer counts, colours, and bounding boxes, with no geometry. The agent then requests only what it needs: entities on one layer or of one type, capped at 500 per call. Full payloads are opt-in.

The remote server runs at https://api.cadlens.co/mcp over Streamable HTTP — nothing to install, always current. The local server is an npm package (cadlens-mcp) that runs on your machine; use it when the agent needs to read CAD files straight off the local filesystem, which a hosted server cannot do.

Yes. A machine-readable server card sits at /.well-known/mcp/server-card.json, agent skills at /.well-known/agent-skills/index.json, an RFC 9727 linkset at /.well-known/api-catalog, and plain-text context at /llms.txt and /llms-full.txt. Pages also return markdown when asked with Accept: text/markdown.

JOIN THE BETA

Get an API key. Parse your first drawing today.

Free tier includes 50 parse requests per month. No credit card required.

Join the beta · Free 50/mo Read the docs
— RELATED

Keep reading.