genrelay-mcp

MCP server for GenRelay — generate video and images from Claude Desktop, Cursor, or any MCP client.

One server, several models: Veo 3.1, Grok Imagine, Omni Flash, Nano Banana Pro/2, GPT Image 2.

Sample outputs

Install

Nothing to install — point your MCP client at it with npx.

Claude Desktop — claude_desktop_config.json:

config.json

{
  "mcpServers": {
    "genrelay": {
      "command": "npx",
      "args": ["-y", "genrelay-mcp"],
      "env": { "GENRELAY_API_KEY": "sk-..." }
    }
  }
}

Cursor — .cursor/mcp.json:

config.json

{
  "mcpServers": {
    "genrelay": {
      "command": "npx",
      "args": ["-y", "genrelay-mcp"],
      "env": { "GENRELAY_API_KEY": "sk-..." }
    }
  }
}

Get a key at genrelay.ai. Restart the client after editing the config.

Tools

Tool	What it does
`generate_video`	Text-to-video and image-to-video. Returns the clip, or a task id if it's still running
`generate_image`	Image generation and editing. Returns the picture inline
`check_job`	Pick up a job by task id
`list_models`	What's available and what each model is for

Then just ask:

Generate an 8-second video of a neon fox running through a rainy city at night, 1080p

About the wait

Video generation takes 1–5 minutes — longer than an MCP tool call is allowed to run. So generate_video waits as long as it safely can, then hands back a task id:

Code

Still generating — this is normal for video.

task id: task_abc123
status: in_progress
progress: 35%

Call check_job with task id "task_abc123" in a minute or two.

That's a normal outcome, not a failure. The job keeps running server-side — use check_job, don't resubmit (resubmitting bills a second time).

Images usually finish inside the budget and come back inline.

Models

Video

Model	Notes
`veo_3_1`	Google Veo 3.1 — highest quality, with audio
`veo_3_1-fl`	first/last frame — supply both endpoints
`veo_3_1-components`	component-guided
`grok-imagine-video-1-5-preview`	xAI Grok Imagine 1.5
`grok-imagine-1-0-video`	xAI Grok Imagine 1.0
`omni-flash`	fast, good for longer clips
`omni_flash_abra_edit`	video editing from a source video

Image — nano-banana-pro, nano-banana-2, gpt-image-2

Tiers: images 1k/2k/4k, Veo video 720p/1080p/4k. Pricing is per tier, and a size matching no tier falls back to the model's base rate — so set tier explicitly when cost matters.

Configuration

Variable
`GENRELAY_API_KEY`	required
`GENRELAY_BASE_URL`	optional, defaults to `https://genrelay.ai/v1`

Also available

Python SDK — pip install genrelay
JavaScript/TypeScript SDK — npm install genrelay
Chat & image edits are OpenAI-compatible: point the official openai package at https://genrelay.ai/v1

Development

Terminal

npm install
npm run build
node test/smoke.mjs   # boots the server and speaks MCP to it

FAQ

What is genrelay-mcp? An MCP server that lets Claude Desktop, Cursor and other MCP clients generate video and images through the GenRelay API.

Which clients work? Any MCP client that can launch a stdio server with npx -y genrelay-mcp, including Claude Desktop and Cursor.

How do I get an API key? Sign up at genrelay.ai and create a key in the console. Set it as GENRELAY_API_KEY.

How is it billed? Prepaid credits in USD, pay as you go. See Pricing.

A video is still running. Do I resubmit? No. Use check_job with the task id. Resubmitting is billed again.

Where is it listed? npm and the official MCP Registry as io.github.gaoruitech/genrelay-mcp.

License

MIT