MODEL PROMPTS

suno-v4 Prompts — 53 curated examples

Examples for using suno-v4 through RunAPI from agent tools or API calls. Copy a prompt, then use it in Claude Code, Codex, Cursor, Windsurf, or your backend.

MODELS

suno-v4

Modality
Music
Provider
Suno
Endpoint
Text To Music
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 music: "Indie folk, 92 BPM, melancholic, fingerstyle acoustic guitar, whispered vocals, 2010s indie style"
1. codex plugin install runapi-mcp@agents
2. Restart Codex
3. Paste this prompt: Generate music: "Indie folk, 92 BPM, melancholic, fingerstyle acoustic guitar, whispered vocals, 2010s indie style"
1. npx @runapi.ai/mcp init cursor
2. Restart Cursor
3. Paste this prompt: Generate music: "Indie folk, 92 BPM, melancholic, fingerstyle acoustic guitar, whispered vocals, 2010s indie style"
1. npx @runapi.ai/mcp init windsurf
2. Restart Windsurf
3. Paste this prompt: Generate music: "Indie folk, 92 BPM, melancholic, fingerstyle acoustic guitar, whispered vocals, 2010s indie style"
curl -X POST https://runapi.ai/api/v1/suno/text_to_music \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "suno-v4",
  "prompt": "Indie folk, 92 BPM, melancholic, fingerstyle acoustic guitar, whispered vocals, 2010s indie style"
}
JSON
import { SunoClient } from "@runapi.ai/suno";

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

const result = await client.textToMusic.run({
  "model": "suno-v4",
  "prompt": "Indie folk, 92 BPM, melancholic, fingerstyle acoustic guitar, whispered vocals, 2010s indie style"
});
console.log(result.id);
require "runapi/suno"

client = RunApi::Suno::Client.new
result = client.text_to_music.run(
  model: "suno-v4",
  prompt: "Indie folk, 92 BPM, melancholic, fingerstyle acoustic guitar, whispered vocals, 2010s indie style"
)
puts result.id
package main

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

func main() {
  body := strings.NewReader("{\"model\":\"suno-v4\",\"prompt\":\"Indie folk, 92 BPM, melancholic, fingerstyle acoustic guitar, whispered vocals, 2010s indie style\"}")
  req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, "https://runapi.ai/api/v1/suno/text_to_music", 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)
}
suno-v4 /api/v1/suno/text_to_music Get API Key
MU
Music
acoustic soul suno-v4

Transform this into a warm acoustic soul version with gentle...

Transform this into a warm acoustic soul version with gentle electric piano, restrained drums, intimate male vocal, steady groove, preserve the original chorus melody, avoid EDM drops and heavy distortion

View API Code
curl -X POST https://runapi.ai/api/v1/suno/text_to_music \
  -H "Authorization: Bearer $RUNAPI_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'JSON'
{
  "model": "suno-v4",
  "prompt": "Transform this into a warm acoustic soul version with gentle electric piano, restrained drums, intimate male vocal, steady groove, preserve the original chorus melody, avoid EDM drops and heavy distortion"
}
JSON
FAQ

Using suno-v4 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.