Examples for using seedance-2.0 through RunAPI from agent tools or API calls. Copy a prompt, then use it in Claude Code, Codex, Cursor, Windsurf, or your backend.
1. claude mcp add runapi -s user -- npx -y @runapi.ai/mcp
2. Restart Claude Code
3. Paste this prompt: Generate a video: "Single continuous cinematic shot, no music. From outside the glass window, the dim camera slowly pushes inward into a pizza shop. A bearded white male employee is baking pizza. He removes the pizza from the oven with a metal tray, places it into a red takeaway box, closes the lid, and then hands it to a customer with a warm smile."
1. codex plugin install runapi-mcp@agents
2. Restart Codex
3. Paste this prompt: Generate a video: "Single continuous cinematic shot, no music. From outside the glass window, the dim camera slowly pushes inward into a pizza shop. A bearded white male employee is baking pizza. He removes the pizza from the oven with a metal tray, places it into a red takeaway box, closes the lid, and then hands it to a customer with a warm smile."
1. npx @runapi.ai/mcp init cursor
2. Restart Cursor
3. Paste this prompt: Generate a video: "Single continuous cinematic shot, no music. From outside the glass window, the dim camera slowly pushes inward into a pizza shop. A bearded white male employee is baking pizza. He removes the pizza from the oven with a metal tray, places it into a red takeaway box, closes the lid, and then hands it to a customer with a warm smile."
1. npx @runapi.ai/mcp init windsurf
2. Restart Windsurf
3. Paste this prompt: Generate a video: "Single continuous cinematic shot, no music. From outside the glass window, the dim camera slowly pushes inward into a pizza shop. A bearded white male employee is baking pizza. He removes the pizza from the oven with a metal tray, places it into a red takeaway box, closes the lid, and then hands it to a customer with a warm smile."
curl -X POST https://runapi.ai/api/v1/seedance/text_to_video \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "seedance-2.0",
"prompt": "Single continuous cinematic shot, no music. From outside the glass window, the dim camera slowly pushes inward into a pizza shop. A bearded white male employee is baking pizza. He removes the pizza from the oven with a metal tray, places it into a red takeaway box, closes the lid, and then hands it to a customer with a warm smile."
}
JSON
import { SeedanceClient } from "@runapi.ai/seedance";
const client = new SeedanceClient({
apiKey: process.env.RUNAPI_API_KEY,
});
const result = await client.textToVideo.run({
"model": "seedance-2.0",
"prompt": "Single continuous cinematic shot, no music. From outside the glass window, the dim camera slowly pushes inward into a pizza shop. A bearded white male employee is baking pizza. He removes the pizza from the oven with a metal tray, places it into a red takeaway box, closes the lid, and then hands it to a customer with a warm smile."
});
console.log(result.id);
require "runapi/seedance"
client = RunApi::Seedance::Client.new
result = client.text_to_video.run(
model: "seedance-2.0",
prompt: "Single continuous cinematic shot, no music. From outside the glass window, the dim camera slowly pushes inward into a pizza shop. A bearded white male employee is baking pizza. He removes the pizza from the oven with a metal tray, places it into a red takeaway box, closes the lid, and then hands it to a customer with a warm smile."
)
puts result.id
package main
import (
"context"
"fmt"
"log"
"net/http"
"os"
"strings"
)
func main() {
body := strings.NewReader("{\"model\":\"seedance-2.0\",\"prompt\":\"Single continuous cinematic shot, no music. From outside the glass window, the dim camera slowly pushes inward into a pizza shop. A bearded white male employee is baking pizza. He removes the pizza from the oven with a metal tray, places it into a red takeaway box, closes the lid, and then hands it to a customer with a warm smile.\"}")
req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, "https://runapi.ai/api/v1/seedance/text_to_video", body)
if err != nil {
log.Fatal(err)
}
req.Header.Set("Authorization", "Bearer "+os.Getenv("RUNAPI_API_KEY"))
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
log.Fatal(err)
}
defer resp.Body.Close()
fmt.Println(resp.Status)
}
seedance-2.0/api/v1/seedance/text_to_videoGet API Key
Studio product shot, matte black wireless earbuds on a reflective acrylic surface, slow 180-degree camera orbit, softbox reflections, premium ecommerce lighting, shallow depth of field, no text, no logo distortion.
Extreme macro of amber liquid pouring into crystal glass in slow motion. Droplets hang in the air, catching backlight. Ice shifts and cracks. Dolly-out reveals full glass and bottle on dark bar counter. No voiceover, only the sound of liquid and ice.
curl -X POST https://runapi.ai/api/v1/seedance/text_to_video \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "seedance-2.0",
"prompt": "Extreme macro of amber liquid pouring into crystal glass in slow motion. Droplets hang in the air, catching backlight. Ice shifts and cracks. Dolly-out reveals full glass and bottle on dark bar counter. No voiceover, only the sound of liquid and ice."
}
JSON
FAQ
Using seedance-2.0 prompts
What is %{model}?
%{model} is available through RunAPI as part of the unified model catalog. These prompts show practical input patterns that agents and backend services can reuse.
How do I use these prompts?
Copy any prompt and paste it into Claude Code, Codex, Cursor, or Windsurf after installing the RunAPI MCP Server. Developers can also copy the API example and send the prompt directly.
Do these prompts cost money to browse?
Browsing and copying prompt examples is free. Generation requests only cost money when you call a RunAPI model with your API key.
Can I adapt the prompts for production?
Yes. Treat each prompt as a starting point, then add your brand rules, output dimensions, safety constraints, and application-specific context before using it in production.