CluserAI developer access
Get your CluserAI API key
Sign in with your CluserAI account to create and manage API keys for the CluserAI API (model: cluserai-3.8oX Lite).
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User Agreement (Turkish draft)
Privacy Policy (Turkish draft)
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Your API keys
Quick start
curl -X POST https://api.cluserai.xyz/api \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{"message": "Hello, CluserAI!"}'
Claude Code Messages gateway
The deployed POST /v1/messages route accepts API keys created here. The adapter can return model-generated tool_use calls for declared client tools. Claude Code itself decides whether to run file or shell tools locally and sends back tool_result; CluserAI never executes those tools or reads your local files. The opaque tool ID must be returned unchanged. The route has a 65,536-token output ceiling. Only mocked protocol tests have run; the Claude Code CLI is not installed here, so end-to-end compatibility is unverified.
ANTHROPIC_BASE_URL=https://api.cluserai.xyz
ANTHROPIC_AUTH_TOKEN=YOUR_CLUSERAI_API_KEY
ANTHROPIC_MODEL=cluserai-3.8ox-lite
Send photos & files
Add images and files (base64) next to your message. Supported: PNG, JPEG, WebP, HEIC, PDF and text files (txt, md, csv, json, html, xml, code). Up to 8 attachments, about 4 MB in total per request. For any other text file, send {"name":"...","text":"..."}.
{
"message": "What is in this photo, and summarize the PDF.",
"images": [ { "mimeType": "image/jpeg", "data": "BASE64..." } ],
"files": [ { "name": "report.pdf", "mimeType": "application/pdf", "data": "BASE64..." } ]
}
JavaScript example (browser):
const b64 = (file) => new Promise((ok) => {
const r = new FileReader();
r.onload = () => ok(r.result.split(",")[1]);
r.readAsDataURL(file);
});
const res = await fetch("https://api.cluserai.xyz/api", {
method: "POST",
headers: { "Content-Type": "application/json", "Authorization": "Bearer YOUR_API_KEY" },
body: JSON.stringify({
message: "Describe this image",
images: [{ mimeType: file.type, data: await b64(file) }]
})
});
console.log((await res.json()).response);
Response
{ "model": "cluserai-3.8ox-lite", "response": "Hi there! How can I help?" }
