Pexafy's answer:

Pexafy is the only search that spans nine free stock photo libraries in one query and ranks the results by meaning rather than by tags. Unsplash, Pexels, Pixabay and six smaller libraries each have their own site, their own API and their own JSON shape; Pexafy indexes them together, removes duplicates, and returns everything in a single schema. It also accepts an image as the query, and exposes the same catalogue to AI assistants through a hosted MCP server — something no other stock photo service offers today.

Pexafy's answer:

Because one search covers what would otherwise be nine, and because the query can be a sentence rather than a keyword: "the quiet after a summer thunderstorm" finds photos that no tag would have matched. For developers, the API key is issued instantly with no application review, where Unsplash caps unapproved applications at 50 requests an hour.

Where Pexafy is not the right answer: if you need raw volume against a single library, Pixabay's free tier is more generous, and we say so on our own comparison page.

Pexafy's answer:

Two groups. People who need a photograph now — bloggers, marketers, designers, teachers — and who are tired of opening three or four stock sites to find one image. And developers building products that need images programmatically: CMS and site builders, newsletter tools, AI writing assistants, no-code workflows. The second group is why the REST API and the MCP server exist.

Pexafy's answer:

It started from a practical annoyance. Covering the free stock libraries properly meant three API keys, three quotas, three JSON shapes and merge code to maintain — and once that was done, the search still matched on the keywords a contributor typed years ago rather than on what the photograph actually shows. Pexafy was built to do that work once: a single index over nine libraries, ranked by meaning, reachable from a browser, an API or an AI assistant.

Pexafy's answer:

Python throughout: FastAPI for the API, Django for the web interface. Search runs on embedding models served on GPU behind a vector index, with Redis for caching and quotas, MySQL and PostgreSQL on the relational side, and Cloudflare in front. The MCP server is a separate Python service with OAuth 2.1.