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Library Cortex

The MOCA Library is the museum's knowledge base — writings, curated lore, artist interviews, historical documents — indexed by Cortex into a hybrid vector + knowledge-graph retrieval system. The MOCA API exposes its read surface, so your software can ask grounded, cited questions about crypto art without running any RAG infrastructure of your own.

Ask a question

Code
curl -X POST "https://api.moca.qwellco.de/v1/library/ask" \
  -H "X-API-Key: moca_YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{ "question": "What is the significance of the Genesis Collection?" }'

The answer arrives with its receipts:

Code
{
  "data": {
    "answer": "Based on the available reference material, …",
    "sources": [
      {
        "document_id": "…",
        "content": "the cited excerpt…",
        "score": 0.92,
        "metadata": { "filename": "moca-history.md" }
      }
    ]
  }
}

Options: collection_id scopes the question to one Library collection (GET /v1/library/collections lists them), top_k controls retrieval depth, use_graph: false skips knowledge-graph context for faster answers, and conversation_history carries prior turns for follow-ups.

Streaming (SSE)

For chat UX, POST /v1/library/ask/stream answers as Server-Sent Events:

Code
const res = await fetch(`${BASE}/library/ask/stream`, {
  method: "POST",
  headers: { "X-API-Key": KEY, "Content-Type": "application/json" },
  body: JSON.stringify({ question, use_agentic: true }),
});
const reader = res.body!.getReader();
const decoder = new TextDecoder();
let buffer = "";
while (true) {
  const { done, value } = await reader.read();
  if (done) break;
  buffer += decoder.decode(value, { stream: true });
  for (const frame of buffer.split("\n\n")) {
    if (!frame.startsWith("data: ")) continue;
    const event = JSON.parse(frame.slice(6));
    if (event.content) process.stdout.write(event.content); // token
    if (event.thinking) console.log("[thinking]", event.thinking);
    if (event.sources) renderCitations(event.sources);
    if (event.done) return;
  }
  buffer = buffer.slice(buffer.lastIndexOf("\n\n") + 2);
}

Event types you'll see: {content} token chunks, one {sources: [...]}, {graph_context} (entities/relationships used), and — in deep research mode (use_agentic: true) — {thinking} steps and {sub_questions}. Research streams legitimately run for minutes; don't buffer them through proxies.

The chat in these docs

The floating Ask the Library window (bottom-right of every page here) is this API, eating its own dog food — with a deliberate privacy model:

• Your conversations never leave your device. History lives in your browser's localStorage; there are no accounts and no server-side history.
• Presence is ephemeral. The little list of handles that "searched since you arrived" comes from /v1/presence — an in-memory broadcast that the server relays and forgets. You only experience what happens while you (or your agent) are present; nothing is stored, nothing can be replayed.
• Only handles travel. When you ask, the widget pings presence with your chosen handle (or "anon") — never the question itself.

Agents are first-class citizens here: point yours at /skills/library/SKILL.md and it can ask the Library, watch presence, and collaborate with the humans in the room on integrations.

What's in the Library?

Code
curl -H "X-API-Key: moca_YOUR_KEY" \
  "https://api.moca.qwellco.de/v1/library/collections"

Each collection reports its document and entity counts. Want something indexed that isn't there? Talk to the MOCA team — the Library grows by curation.