name: fal-ai-media
description: Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.
origin: ECC

fal.ai Media Generation

Generate images, videos, and audio using fal.ai models via MCP.

When to Activate

• User wants to generate images from text prompts
• Creating videos from text or images
• Generating speech, music, or sound effects
• Any media generation task
• User says "generate image", "create video", "text to speech", "make a thumbnail", or similar

MCP Requirement

fal.ai MCP server must be configured. Add to ~/.claude.json:

"fal-ai": {
  "command": "npx",
  "args": ["-y", "fal-ai-mcp-server"],
  "env": { "FAL_KEY": "YOUR_FAL_KEY_HERE" }
}

Get an API key at fal.ai.

MCP Tools

The fal.ai MCP provides these tools:

• search — Find available models by keyword
• find — Get model details and parameters
• generate — Run a model with parameters
• result — Check async generation status
• status — Check job status
• cancel — Cancel a running job
• estimate_cost — Estimate generation cost
• models — List popular models
• upload — Upload files for use as inputs

Image Generation

Nano Banana 2 (Fast)

Best for: quick iterations, drafts, text-to-image, image editing.

generate(
  app_id: "fal-ai/nano-banana-2",
  input_data: {
    "prompt": "a futuristic cityscape at sunset, cyberpunk style",
    "image_size": "landscape_16_9",
    "num_images": 1,
    "seed": 42
  }
)

Nano Banana Pro (High Fidelity)

Best for: production images, realism, typography, detailed prompts.

generate(
  app_id: "fal-ai/nano-banana-pro",
  input_data: {
    "prompt": "professional product photo of wireless headphones on marble surface, studio lighting",
    "image_size": "square",
    "num_images": 1,
    "guidance_scale": 7.5
  }
)

Common Image Parameters

Image Editing

Use Nano Banana 2 with an input image for inpainting, outpainting, or style transfer:

# First upload the source image
upload(file_path: "/path/to/image.png")

# Then generate with image input
generate(
  app_id: "fal-ai/nano-banana-2",
  input_data: {
    "prompt": "same scene but in watercolor style",
    "image_url": "<uploaded_url>",
    "image_size": "landscape_16_9"
  }
)

Video Generation

Seedance 1.0 Pro (ByteDance)

Best for: text-to-video, image-to-video with high motion quality.

generate(
  app_id: "fal-ai/seedance-1-0-pro",
  input_data: {
    "prompt": "a drone flyover of a mountain lake at golden hour, cinematic",
    "duration": "5s",
    "aspect_ratio": "16:9",
    "seed": 42
  }
)

Kling Video v3 Pro

Best for: text/image-to-video with native audio generation.

generate(
  app_id: "fal-ai/kling-video/v3/pro",
  input_data: {
    "prompt": "ocean waves crashing on a rocky coast, dramatic clouds",
    "duration": "5s",
    "aspect_ratio": "16:9"
  }
)

Veo 3 (Google DeepMind)

Best for: video with generated sound, high visual quality.

generate(
  app_id: "fal-ai/veo-3",
  input_data: {
    "prompt": "a bustling Tokyo street market at night, neon signs, crowd noise",
    "aspect_ratio": "16:9"
  }
)

Image-to-Video

Start from an existing image:

generate(
  app_id: "fal-ai/seedance-1-0-pro",
  input_data: {
    "prompt": "camera slowly zooms out, gentle wind moves the trees",
    "image_url": "<uploaded_image_url>",
    "duration": "5s"
  }
)

Video Parameters

Audio Generation

CSM-1B (Conversational Speech)

Text-to-speech with natural, conversational quality.

generate(
  app_id: "fal-ai/csm-1b",
  input_data: {
    "text": "Hello, welcome to the demo. Let me show you how this works.",
    "speaker_id": 0
  }
)

ThinkSound (Video-to-Audio)

Generate matching audio from video content.

generate(
  app_id: "fal-ai/thinksound",
  input_data: {
    "video_url": "<video_url>",
    "prompt": "ambient forest sounds with birds chirping"
  }
)

ElevenLabs (via API, no MCP)

For professional voice synthesis, use ElevenLabs directly:

import os
import requests

resp = requests.post(
    "https://api.elevenlabs.io/v1/text-to-speech/<voice_id>",
    headers={
        "xi-api-key": os.environ["ELEVENLABS_API_KEY"],
        "Content-Type": "application/json"
    },
    json={
        "text": "Your text here",
        "model_id": "eleven_turbo_v2_5",
        "voice_settings": {"stability": 0.5, "similarity_boost": 0.75}
    }
)
with open("output.mp3", "wb") as f:
    f.write(resp.content)

VideoDB Generative Audio

If VideoDB is configured, use its generative audio:

# Voice generation
audio = coll.generate_voice(text="Your narration here", voice="alloy")

# Music generation
music = coll.generate_music(prompt="upbeat electronic background music", duration=30)

# Sound effects
sfx = coll.generate_sound_effect(prompt="thunder crack followed by rain")

Cost Estimation

Before generating, check estimated cost:

estimate_cost(
  estimate_type: "unit_price",
  endpoints: {
    "fal-ai/nano-banana-pro": {
      "unit_quantity": 1
    }
  }
)

Model Discovery

Find models for specific tasks:

search(query: "text to video")
find(endpoint_ids: ["fal-ai/seedance-1-0-pro"])
models()

Tips

• Use seed for reproducible results when iterating on prompts
• Start with lower-cost models (Nano Banana 2) for prompt iteration, then switch to Pro for finals
• For video, keep prompts descriptive but concise — focus on motion and scene
• Image-to-video produces more controlled results than pure text-to-video
• Check estimate_cost before running expensive video generations

Related Skills

• videodb — Video processing, editing, and streaming
• video-editing — AI-powered video editing workflows
• content-engine — Content creation for social platforms