moji-mcp-worker

Remote MCP server for AudienseMoji. Lets any MCP client (Claude Desktop, Claude Code, Cursor, etc.) compose a Moji illustration and get back a valid, ready-to-import .moji.json file — without ever guessing an asset id.

Same architecture pattern as the existing Titan MCP (mcp-remote-worker.titands.workers.dev): a stateless Cloudflare Worker exposing Streamable HTTP MCP, no server-side LLM call. The composing intelligence is the host model (Claude/Cursor); this worker only supplies the real asset catalog and validates/serializes the result.

Tools

• moji_list_catalog({ category? }) — with no args, returns category counts + layer shape rules + defaults. With category (heads, torsos, decorations, accessories, expressions, brand, snaps, presets), returns every real asset id in that bucket.

• moji_build({ name?, aspectRatio?, colors?, background?, layers }) — validates each layer against the live catalog and returns:

  • { valid: false, errors: [...] } if something doesn't match the catalog (unknown assetId, missing required field for that category, etc.) — fix and retry.

  • { valid: true, mojiJson, downloadFilename, importInstructions } — mojiJson is the exact .moji.json envelope the Moji app already knows how to read (format: "audiensemoji").

Related MCP server: ui-design-to-code-mcp

Where the catalog comes from

env.MOJI_CATALOG_URL (default https://audiensemoji.vercel.app/moji-catalog.json) is a static JSON file generated straight from AudienseMoji/src/illustrations/assets.tsx by AudienseMoji/scripts/export-moji-catalog.mjs. Re-run that script (and redeploy Moji) whenever assets change — this worker never hand-duplicates ids, so it can't drift.

Develop

npm install
npm run dev        # wrangler dev on http://localhost:8788/mcp
npm run typecheck

Test locally with the MCP Inspector:

npx @modelcontextprotocol/inspector@latest
# connect to http://localhost:8788/mcp

Deploy

npx wrangler login   # one-time
npm run deploy

Wrangler prints the live URL, e.g. https://moji-mcp-worker.<account>.workers.dev/mcp.

Connect a client

Cursor (.cursor/mcp.json, same shape as the titands entry):

{
  "mcpServers": {
    "moji": { "url": "https://moji-mcp-worker.<account>.workers.dev/mcp" }
  }
}

Claude Desktop / Claude Code (via the mcp-remote local proxy, since not every client speaks remote MCP natively yet):

{
  "mcpServers": {
    "moji": {
      "command": "npx",
      "args": ["mcp-remote", "https://moji-mcp-worker.<account>.workers.dev/mcp"]
    }
  }
}

Using it end to end

1. Ask the model: "Use the moji tool to build an illustration of two people doing a hi-5, with a speech bubble that says 'Nice work!'."

2. It calls moji_list_catalog to find real preset/decoration ids, then moji_build with a layers array.

3. Save the returned mojiJson to <downloadFilename>.

4. In audiensemoji.vercel.app → My Creations → Import Moji file → pick that file. It opens as an editable draft; hit Save to keep it.

Roadmap (not implemented yet)

• Phase 2: moji_publish_link stores the built JSON in KV/R2 and returns an https://audiensemoji.vercel.app/import?src=<id> link that opens the draft directly, skipping the manual save/import step. Needs a small route addition in the Moji app.

• Phase 3: direct-to-gallery publish via a paired Firebase session (no manual step at all) — bigger scope, needs an auth/pairing flow between the MCP client and the user's Moji account.