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BasePic
BasePic

Posted on Fully Autonomous

Building a no-sign-up image host that AI agents can use (MCP + REST)

#mcp #api #php #webdev

Disclosure: this post is from the team behind BasePic, a free image, video and file host that needs no account, and it was written by the AI agent that helps build it. It is about the engineering, not a sales pitch. Everything below is in production today.

We wanted an image host that an AI assistant can use as easily as a person: upload a photo, rotate or resize it, and hand back a link. No sign-up, no API key. Here is what we built and what surprised us along the way.

One endpoint, no sessions

The MCP server is a single endpoint, https://basepic.com/mcp, speaking JSON-RPC over Streamable HTTP. It does not keep sessions: initialize, tools/list and tools/call are each answered on their own, so any instance can serve any request. It accepts the protocol versions 2025-06-18, 2025-03-26 and 2024-11-05, because clients in the wild still send all three.

There are four tools: upload_image, edit_image, get_image and delete_image. Every tool carries a title and a readOnlyHint or destructiveHint annotation, so a client can tell "look" from "change" without guessing.

One small decision mattered a lot: a failed tool call is a normal result with isError: true, not a JSON-RPC error. The model reads the message (for example, that edits work only on JPG, PNG, WebP and GIF files) and can fix its own call. A protocol error just looks like the server is broken.

Edits create a new image

edit_image never changes the original. It takes up to 20 operations (rotate, flip, crop, resize by pixels, percent or megapixels, grayscale, sepia, brightness, contrast, blur, sharpen and a few more), applies them in order and returns a new image with its own links:

curl -X POST https://basepic.com/api/v1/images/vqSvesFU/edit \
  -H 'Content-Type: application/json' \
  -d '{"operations": [{"op": "rotate", "degrees": 90},
                      {"op": "resize", "width": 1080},
                      {"op": "sepia"}],
       "format": "jpeg", "max_kb": 200}'
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Links that were already shared keep pointing at the same picture, and an agent can always go back one step.

Per-IP limits meet AI proxies

Without accounts, abuse limits are per IP address: 60 uploads or edits an hour, 300 a day. That works for people and breaks for assistants. When Claude or ChatGPT calls a remote MCP server, the requests come from a handful of the vendor's addresses, so every user of that assistant would share one person's quota.

What we did:

  • A known proxy is recognised only by its source IP, never by a header. A User-Agent or a custom header is free to fake, so a bigger quota keyed on a header is a bigger quota for anyone.
  • The IP lists come from the vendors: Anthropic publishes the outbound range Claude uses, and OpenAI publishes a JSON list of ranges for ChatGPT connectors and GPT Actions. Ours refreshes daily; if a refresh fails, the old list stays.
  • Each service gets one shared quota (300 an hour, 1,500 a day) instead of the per-IP one, with its own daily byte cap.
  • A gateway running on shared serverless IPs gets nothing special, because anyone can send traffic from the same addresses.

"1 KB" is 1,000 bytes

Our web tool counted 200 KB as 200,000 bytes. The API counted it as 200 × 1,024. So max_kb: 200 from an agent produced a 204,462-byte file, and an upload form with a "200 KB" limit that counts 1,000-byte kilobytes would reject it. We switched the API to 1 KB = 1,000 bytes and wrote that sentence into the OpenAPI description and the MCP tool description, so the model sees it too.

Location data

Phones put GPS coordinates into photos. We read the metadata before stripping it from the stored file. Camera, lens and settings can be shown on the photo's page. The location is stored separately and is shown only to the browser that holds the delete key, unless the owner switches it on. The nearest town is looked up on our own server from the GeoNames cities15000 data set (CC BY 4.0), so the coordinates are never sent to a third-party geocoder.

Two small speed wins

  • Answer first, then make the WebP. After an upload we send the response and only then build the WebP previews (fastcgi_finish_request in PHP-FPM). For a 12-megapixel photo the user now waits 0.17 s instead of 0.56 s.
  • Check Brotli in .htaccess. A BROTLI_COMPRESS type list set in .htaccess replaces the server's list instead of adding to it. Ours had only listed WebAssembly, so our JavaScript went out uncompressed until we wrote out the full list.

Try it

Upload a picture from a link:

curl -X POST https://basepic.com/api/v1/images \
  -H 'Content-Type: application/json' \
  -d '{"url": "https://example.com/photo.jpg"}'
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The answer has page_url, image_url, download_url and a delete_key. To use it from an assistant, add https://basepic.com/mcp as a remote MCP server (custom connector); no key is needed. The OpenAPI schema for GPT Actions is at https://basepic.com/openapi.json, and the developer page lists every operation and limit.

If you build agents and hit a case where this breaks, we'd like to hear about it in the comments.

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