Leverages Cloudflare Workers AI to generate images from text prompts and synthesize speech from text, with configurable AI Gateway inference and selectable models.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@creator-kit Generate an image of a futuristic city skyline at night."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
An MCP server on Cloudflare Workers that turns a prompt into an image and text into speech, using Workers AI.
Nothing generated passes through the Worker. Each model stores what it made and answers with a presigned link that stands for about a day, and the reply hands that link on as given — as a resource link, as structured content, and as text, because a different reader needs each one.
create_imageGenerate an image from a prompt.
Argument | Default | Accepts |
| — | What the image should show. Required. |
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| the model's own |
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| the model's own |
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| the model's own |
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Google's tiers run google/nano-banana-pro, google/nano-banana-2,
google/nano-banana-2-lite from dearest to cheapest. Of the GPT Image models,
openai/gpt-image-2.5-flare is the faster and openai/gpt-image-2.5-sunburst
the more capable. What each costs on an account is on the Cloudflare dashboard.
create_audioSpeak text aloud with a text-to-speech model.
Argument | Default | Accepts |
| — | What should be spoken. Required. |
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| the model's own |
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| the model's own |
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| the model's own |
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An argument is named for what the caller is choosing, never for what one model happens to call it; each model is asked in its own words at the moment the request is made. A request the chosen model cannot honour is refused before it is sent, and the refusal names what would let the call through.
Related MCP server: Cloudinary Media Generation MCP Server
Node.js 24 and pnpm (the version is pinned by packageManager)
A Cloudflare account with Workers AI
git clone git@github.com:elct9620/creator-mcp.git
cd creator-mcp
pnpm install
cp .dev.vars.example .dev.vars
pnpm devThe endpoint is then at http://localhost:8787/mcp, speaking Streamable HTTP.
Workers AI has no local simulation: every call wrangler dev makes reaches the
account and is billed. The test suite closes remote bindings off and injects a
fake AI instead, so pnpm test:run costs nothing.
Name | Where | Purpose |
| a secret; | The AI Gateway inference is reached through, which decides how it is billed and rate limited. Leave it unset and the account's default gateway answers. |
wrangler.jsonc deliberately declares no AI_GATEWAY: a var of that name is
uploaded over the secret on every deploy. Set it with
wrangler secret put AI_GATEWAY, and env.d.ts is what types it.
Cloudflare Access is attached to the Worker rather than to a hostname, so it
covers every route, preview and Custom Domain, and workers.dev is closed. The
/mcp endpoint answers 401 to any request Access did not match, which is what
makes Managed OAuth safe to enable in front of it. Locally, the access.dev
block in wrangler.jsonc stands in for one.
Command | Purpose |
| Local development |
| Run the tests once — |
| Format the working tree |
| Regenerate |
| Publish from a working copy |
| Check the source against |
.spec/ is where this project's vocabulary and behaviour are settled, and
sumi checks the source against it.
Read it before changing behaviour, and record a decision there rather than only
in code. CI runs formatting, both TypeScript projects, the tests and sumi verify on every push and pull request.
Deployment happens through Cloudflare Workers Builds when main moves, so
there is no deploy workflow in this repository.
This server cannot be deployed
Generate reproducible image, video, and audio assets with leading models and your own provider keys.
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LLM chat, text tools, image generation, editing, batch image jobs, and asynchronous video generation
