MODEL PROMPTS

runway Prompts — 3 curated examples

Examples for using runway through RunAPI from agent tools or API calls. Copy a prompt, then use it in Claude Code, Codex, Cursor, Windsurf, or your backend.

MODELS

runway

Modality
Video
Provider
Runway
Endpoint
Text To Video
View model details and pricing →
1. claude mcp add runapi -s user -- npx -y @runapi.ai/mcp
2. Restart Claude Code
3. Paste this prompt: Generate a video: "A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
1. codex plugin install runapi-mcp@agents
2. Restart Codex
3. Paste this prompt: Generate a video: "A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
1. npx @runapi.ai/mcp init cursor
2. Restart Cursor
3. Paste this prompt: Generate a video: "A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
1. npx @runapi.ai/mcp init windsurf
2. Restart Windsurf
3. Paste this prompt: Generate a video: "A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
curl -X POST https://runapi.ai/api/v1/runway/text_to_video \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "runway",
  "prompt": "A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
}
JSON
import { RunwayClient } from "@runapi.ai/runway";

const client = new RunwayClient({
  apiKey: process.env.RUNAPI_API_KEY,
});

const result = await client.textToVideo.run({
  "model": "runway",
  "prompt": "A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
});
console.log(result.id);
require "runapi/runway"

client = RunApi::Runway::Client.new
result = client.text_to_video.run(
  model: "runway",
  prompt: "A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean."
)
puts result.id
package main

import (
  "context"
  "fmt"
  "log"
  "net/http"
  "os"
  "strings"
)

func main() {
  body := strings.NewReader("{\"model\":\"runway\",\"prompt\":\"A glowing ocean at night time with bioluminescent creatures under water. The camera starts with a macro close-up of a glowing jellyfish and then expands to reveal the entire ocean lit up with various glowing colors under a starry sky. Camera Movement: Begin with a macro shot of the jellyfish, then gently pull back and up to showcase the glowing ocean.\"}")
  req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, "https://runapi.ai/api/v1/runway/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)
}
runway /api/v1/runway/text_to_video Get API Key
VI
Video
cinematic runway

Hyperspeed timelapse: The camera ascends from street level t...

Hyperspeed timelapse: The camera ascends from street level to a rooftop, showcasing a city's transformation from day to night. Neon signs flicker to life, traffic becomes streams of light, and skyscrapers illuminate against the darkening sky.

View API Code
curl -X POST https://runapi.ai/api/v1/runway/text_to_video \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "runway",
  "prompt": "Hyperspeed timelapse: The camera ascends from street level to a rooftop, showcasing a city's transformation from day to night. Neon signs flicker to life, traffic becomes streams of light, and skyscrapers illuminate against the darkening sky."
}
JSON
VI
Video
cinematic runway

Cinematic dolly — abandoned library

Slow forward dolly shot through an abandoned grand library. The camera glides at waist height between towering bookshelves that stretch to a vaulted ceiling covered in peeling frescoes. Dust motes float in shafts of golden light entering through tall arched windows with broken panes. Books are scattered on the floor, some open with pages curling. Ivy creeps through a crack in the far wall. The movement is perfectly smooth and linear, never deviating from the central aisle. Atmospheric, melancholic mood. Warm color palette with deep shadows in the shelf recesses.

View API Code
curl -X POST https://runapi.ai/api/v1/runway/text_to_video \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "runway",
  "prompt": "Slow forward dolly shot through an abandoned grand library. The camera glides at waist height between towering bookshelves that stretch to a vaulted ceiling covered in peeling frescoes. Dust motes float in shafts of golden light entering through tall arched windows with broken panes. Books are scattered on the floor, some open with pages curling. Ivy creeps through a crack in the far wall. The movement is perfectly smooth and linear, never deviating from the central aisle. Atmospheric, melancholic mood. Warm color palette with deep shadows in the shelf recesses."
}
JSON
FAQ

Using runway 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.