homotope

Vectorize images into clean SVG, PDF, EPS or DXF files, and check a DXF before laser or vinyl cutting.

View in the Claude registry
Primary Subcategory
Pending
Integration details

Description

Homotope turns raster images (PNG, JPEG) into clean vector files. From Claude, send a logo, an illustration, a scan or a sketch: Homotope traces it on its server and returns an SVG, or a PDF, EPS or DXF (one layer per colour, colour separations on request). Before you send a DXF to a laser, a vinyl cutter or a plotter, the “Ready to cut?” check reports open contours, double cuts, overlaps and details finer than your tool. Every job through Claude is a server job: the image is sent to Homotope and the job counts against your Homotope Pro quota, then credits; there is no free trial this way. In the browser, at homotope.app, tracing is free and nothing is sent. Six tools: vectorize_image, get_job, get_svg, get_result, check_cut, list_vectorizations. Read-only tools never write; vectorize_image creates a job and never deletes anything.

Integration type
Connector
Verification status
Community connector
Platform
Claude
Category
Content & Design

The broad Category that contains the Primary Subcategory.

Primary Subcategory
Pending

The Primary Subcategory used for this profile’s headline score.

Secondary Subcategories
None listed

Other Subcategories where the Integration is listed.

Access
Account required
First tracked
2026-10-10
Tool count
6
Geography
US
Agent DiscoverabilityClaude Discoverability Score

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Primary Subcategory

Competitive lineup

No Primary Subcategory assigned yetOnce homotope has a Primary Subcategory, the Plugins and Connectors it competes with will appear here with their scores.
Tools

6 tools agents can invoke

Recommended guideHow to get your Claude Connector organically discoveredFollow the practical steps agents use to find, shortlist, and choose your Connector.Read guide
FAQs

homotope Claude Connector FAQ

How the directory, categories and Discoverability Score work.

Read the methodology
How do I improve homotope's Claude Connector discoverability?

The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.

Where is this profile measured?

This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.