Getting Started with Seedance MCP in Cursor

If you already use Cursor as your coding workspace, the awkward part of making short demo videos is not creativity; it is leaving the editor, opening another tool, up references, and then bringing the result back into your project.

This guide shows a small, practical setup: connect the Seedance MCP server to Cursor so you can ask your assistant to generate short text-to-video or image-to-video clips from inside the same project where you write docs, landing pages, and product demos.

Seedance is an AI video generation model from ByteDance. Through the Seedance MCP server, Cursor can call a single video-generation tool, seedance_generate_video, using natural language. The useful part is not that it replaces a full video editor. The useful part is that it can create quick motion assets while you are still in the builder flow.

The source document describes three practical use cases:

generate_audio: true when you want the result to include ambient sound effects. The MCP server exposes one tool:

seedance_generate_video

That tool is described as supporting text/image to video generation. So the safe mental model is: use Cursor chat to provide a prompt, optionally include a reference image when your client supports passing one, and let the MCP server handle the video-generation call.

Cursor reads MCP servers from a project-level config file. For this integration, create this file in your repository:

.cursor/mcp.json

Add the Seedance MCP server configuration:

{
  "mcpServers": {
    "seedance": {
      "type": "http",
      "url": "https://seedance.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer yourToken"
      }
    }
  }
}

The important fields are all in that small JSON block:

type: http url: https://seedance.mcp.acedata.cloud/mcp Authorization: Bearer yourToken After saving the file, Cursor should automatically recognize and connect to the MCP server. In a real project, never commit a config file that contains a real token. Keep it local, ignore it, or use your team's preferred secret-management pattern.

Before using the server, you need an Ace Data Cloud API Token. The document describes a simple flow: open the Ace Data Cloud platform, sign in with GitHub, Google, or WeChat, and copy the API Token from the homepage after logging in.

The same token can be used across Ace Data Cloud MCP servers, so you do not need a separate token just for Seedance. In the JSON above, replace yourToken with your actual token:

"Authorization": "Bearer yourToken"

Again: do not paste a real token into a public repository, issue, blog comment, screenshot, or shared recording.

Once Cursor shows the server as connected, use Composer or Chat with a concrete prompt. For example, if you are building a product page and want a small hero motion concept, you could ask:

Generate a 3-second video: on a white background, blue lines gradually outline the shape of a tech logo, and finally, the logo is fully presented.

That prompt mirrors the logo animation scenario in the documentation. It is specific enough to be useful: duration, background, motion, color, subject, and final state are all included.

For UI demos, I would write prompts in the same structured way:

Use this app screenshot as the starting screen, generate a video showing the effect of users sliding and browsing on the interface.

The key is to describe the motion, not only the static object. “A dashboard screenshot” is vague. “A user scrolls through cards, opens one panel, and the camera slightly zooms toward the selected chart” is much easier for a video model to follow.

The source doc also calls out videos with sound. For a café coding scene, the example prompt is:

Generate a video of a café scene, with someone coding in front of a laptop, with ambient sound effects.

When you want the video to include sound effects, set:

{
  "generate_audio": true
}

Use this intentionally. Audio makes sense for atmosphere, explainers, and social clips. For product UI mockups, silent video is often easier to reuse because you can add narration or captions later.

I would use this setup for disposable-but-useful assets: a README demo clip, a landing-page motion test, a quick logo animation, or a product walkthrough concept before investing time in After Effects or a full editing workflow.

The benefit is context. Cursor already knows the project you are working on. By connecting Seedance through MCP, you can go from implementation to visual demo without switching tools. Start with one short prompt, inspect the result, then iterate on the motion and constraints.

The official setup guide is here: Cursor with Seedance MCP.