Gemini ⇄ Claude MCP Bridge

A tiny private MCP server that lets Claude generate images with Google Gemini / Imagen. Deploy it once on Vercel, add its URL as a custom connector in Claude, and Claude can call generate_image directly.

Exposed tool: generate_image(prompt, aspect_ratio?) → returns a PNG.

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STEP 1 — Get a Gemini API key

1. Go to https://aistudio.google.com/apikey
2. Click Create API key and copy it.

STEP 2 — Deploy on Vercel (CLI, fastest)

npm install
npm i -g vercel
vercel            # log in, accept defaults → gives a *.vercel.app URL
vercel env add GEMINI_API_KEY     # paste your key, choose Production
vercel --prod     # redeploy with the key

(Alternative: push this folder to GitHub → import in the Vercel dashboard → add the env var GEMINI_API_KEY under Settings → Environment Variables → Redeploy.)

STEP 3 — Get your connector URL

Your MCP endpoint is your deployment URL + /api/mcp, e.g.:

https://gemini-mcp-bridge-xxxx.vercel.app/api/mcp

STEP 4 — Add it to Claude

1. Claude → Customize → Connectors.
2. Click + → Add custom connector.
3. Paste the /api/mcp URL → Add.
4. In the chat, open the + menu → Connectors → toggle it on.

STEP 5 — Use it

Tell Claude: "Gemini is connected — generate the 6 frames." Claude will call generate_image for each prompt and receive the images directly.

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Notes

• Model id: defaults to imagen-4.0-generate-001. If you get a "model not found" error, copy the current Imagen id from AI Studio into the GEMINI_IMAGE_MODEL env var.
• Timeout: image generation can take a few seconds; the route allows up to 60s.
• Auth: this server is open by default (anyone with the URL can spend your Gemini quota). Keep the URL private. For production, wrap the handler with withMcpAuth (see Vercel MCP docs) or add OAuth.
• Cost: each generation consumes your Google AI Studio quota/billing, not Claude.