Examples for using nano-banana-pro 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 an image: "Architectural photograph of a striking modernist house built into a hillside. The structure features a massive cantilevered concrete volume extending over a slope covered in wild grasses. Floor-to-ceiling glass walls on the underside of the cantilever create a floating living space. Raw board-formed concrete with visible wood grain texture. A narrow infinity pool runs along the front edge, reflecting overcast sky. Surrounded by mature eucalyptus trees. Shot from a low angle emphasizing the dramatic overhang. Architectural Digest editorial style, golden hour lighting."
1. codex plugin install runapi-mcp@agents
2. Restart Codex
3. Paste this prompt: Generate an image: "Architectural photograph of a striking modernist house built into a hillside. The structure features a massive cantilevered concrete volume extending over a slope covered in wild grasses. Floor-to-ceiling glass walls on the underside of the cantilever create a floating living space. Raw board-formed concrete with visible wood grain texture. A narrow infinity pool runs along the front edge, reflecting overcast sky. Surrounded by mature eucalyptus trees. Shot from a low angle emphasizing the dramatic overhang. Architectural Digest editorial style, golden hour lighting."
1. npx @runapi.ai/mcp init cursor
2. Restart Cursor
3. Paste this prompt: Generate an image: "Architectural photograph of a striking modernist house built into a hillside. The structure features a massive cantilevered concrete volume extending over a slope covered in wild grasses. Floor-to-ceiling glass walls on the underside of the cantilever create a floating living space. Raw board-formed concrete with visible wood grain texture. A narrow infinity pool runs along the front edge, reflecting overcast sky. Surrounded by mature eucalyptus trees. Shot from a low angle emphasizing the dramatic overhang. Architectural Digest editorial style, golden hour lighting."
1. npx @runapi.ai/mcp init windsurf
2. Restart Windsurf
3. Paste this prompt: Generate an image: "Architectural photograph of a striking modernist house built into a hillside. The structure features a massive cantilevered concrete volume extending over a slope covered in wild grasses. Floor-to-ceiling glass walls on the underside of the cantilever create a floating living space. Raw board-formed concrete with visible wood grain texture. A narrow infinity pool runs along the front edge, reflecting overcast sky. Surrounded by mature eucalyptus trees. Shot from a low angle emphasizing the dramatic overhang. Architectural Digest editorial style, golden hour lighting."
curl -X POST https://runapi.ai/api/v1/nano_banana/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "nano-banana-pro",
"prompt": "Architectural photograph of a striking modernist house built into a hillside. The structure features a massive cantilevered concrete volume extending over a slope covered in wild grasses. Floor-to-ceiling glass walls on the underside of the cantilever create a floating living space. Raw board-formed concrete with visible wood grain texture. A narrow infinity pool runs along the front edge, reflecting overcast sky. Surrounded by mature eucalyptus trees. Shot from a low angle emphasizing the dramatic overhang. Architectural Digest editorial style, golden hour lighting."
}
JSON
import { NanoBananaClient } from "@runapi.ai/nano-banana";
const client = new NanoBananaClient({
apiKey: process.env.RUNAPI_API_KEY,
});
const result = await client.textToImage.run({
"model": "nano-banana-pro",
"prompt": "Architectural photograph of a striking modernist house built into a hillside. The structure features a massive cantilevered concrete volume extending over a slope covered in wild grasses. Floor-to-ceiling glass walls on the underside of the cantilever create a floating living space. Raw board-formed concrete with visible wood grain texture. A narrow infinity pool runs along the front edge, reflecting overcast sky. Surrounded by mature eucalyptus trees. Shot from a low angle emphasizing the dramatic overhang. Architectural Digest editorial style, golden hour lighting."
});
console.log(result.id);
require "runapi/nano_banana"
client = RunApi::NanoBanana::Client.new
result = client.text_to_image.run(
model: "nano-banana-pro",
prompt: "Architectural photograph of a striking modernist house built into a hillside. The structure features a massive cantilevered concrete volume extending over a slope covered in wild grasses. Floor-to-ceiling glass walls on the underside of the cantilever create a floating living space. Raw board-formed concrete with visible wood grain texture. A narrow infinity pool runs along the front edge, reflecting overcast sky. Surrounded by mature eucalyptus trees. Shot from a low angle emphasizing the dramatic overhang. Architectural Digest editorial style, golden hour lighting."
)
puts result.id
package main
import (
"context"
"fmt"
"log"
"net/http"
"os"
"strings"
)
func main() {
body := strings.NewReader("{\"model\":\"nano-banana-pro\",\"prompt\":\"Architectural photograph of a striking modernist house built into a hillside. The structure features a massive cantilevered concrete volume extending over a slope covered in wild grasses. Floor-to-ceiling glass walls on the underside of the cantilever create a floating living space. Raw board-formed concrete with visible wood grain texture. A narrow infinity pool runs along the front edge, reflecting overcast sky. Surrounded by mature eucalyptus trees. Shot from a low angle emphasizing the dramatic overhang. Architectural Digest editorial style, golden hour lighting.\"}")
req, err := http.NewRequestWithContext(context.Background(), http.MethodPost, "https://runapi.ai/api/v1/nano_banana/text_to_image", 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)
}
nano-banana-pro/api/v1/nano_banana/text_to_imageGet API Key
Architectural photograph of a striking modernist house built into a hillside. The structure features a massive cantilevered concrete volume extending over a slope covered in wild grasses. Floor-to-ceiling glass walls on the underside of the cantilever create a floating living space. Raw board-formed concrete with visible wood grain texture. A narrow infinity pool runs along the front edge, reflecting overcast sky. Surrounded by mature eucalyptus trees. Shot from a low angle emphasizing the dramatic overhang. Architectural Digest editorial style, golden hour lighting.
curl -X POST https://runapi.ai/api/v1/nano_banana/text_to_image \
-H "Authorization: Bearer $RUNAPI_KEY" \
-H "Content-Type: application/json" \
--data-binary @- <<'JSON'
{
"model": "nano-banana-pro",
"prompt": "Architectural photograph of a striking modernist house built into a hillside. The structure features a massive cantilevered concrete volume extending over a slope covered in wild grasses. Floor-to-ceiling glass walls on the underside of the cantilever create a floating living space. Raw board-formed concrete with visible wood grain texture. A narrow infinity pool runs along the front edge, reflecting overcast sky. Surrounded by mature eucalyptus trees. Shot from a low angle emphasizing the dramatic overhang. Architectural Digest editorial style, golden hour lighting."
}
JSON
FAQ
Using nano-banana-pro 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.