fal-ai-media
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.
- License 许可
- MIT
- 最近更新
- 2026-11-02
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01 前言 Front Matter
- name
- fal-ai-media
- origin
- ECC
- 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.
03 SKILL.md 正文
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 keywordfind— Get model details and parametersgenerate— Run a model with parametersresult— Check async generation statusstatus— Check job statuscancel— Cancel a running jobestimate_cost— Estimate generation costmodels— List popular modelsupload— 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
| Param | Type | Options | Notes |
|---|---|---|---|
prompt |
string | required | Describe what you want |
image_size |
string | square, portrait_4_3, landscape_16_9, portrait_16_9, landscape_4_3 |
Aspect ratio |
num_images |
number | 1-4 | How many to generate |
seed |
number | any integer | Reproducibility |
guidance_scale |
number | 1-20 | How closely to follow the prompt (higher = more literal) |
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
| Param | Type | Options | Notes |
|---|---|---|---|
prompt |
string | required | Describe the video |
duration |
string | "5s", "10s" |
Video length |
aspect_ratio |
string | "16:9", "9:16", "1:1" |
Frame ratio |
seed |
number | any integer | Reproducibility |
image_url |
string | URL | Source image for image-to-video |
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
seedfor 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_costbefore running expensive video generations
Related Skills
videodb— Video processing, editing, and streamingvideo-editing— AI-powered video editing workflowscontent-engine— Content creation for social platforms
04 同仓库更多 Skills
clarify-requirements
Resolve genuine pre-execution ambiguity by scanning repo context, generating 1-6 grounded options, and asking 1-3 focused questions via AskUserQuestion. NOT for mid-task use (injection risk); NOT when the goal is already unambiguous; use to disambiguate vague prompts before any file edits.
openmm-md
Run FREE, open-source, Windows-native GPU molecular dynamics via the openmm-md MCP (OpenMM + CUDA on the local NVIDIA GPU). Use for protein / protein-ligand MD when you want a free stack or are on Windows without a Schrodinger license. Covers the full workflow (prepare, solvate, minimize, equilibrate, production, analyze, mmgbsa) AND an honest decision guide vs Schrodinger Desmond, including how to run Desmond legitimately on Linux or a cloud GPU with a real license. This is a deliberately LESSER free alternative and does NOT replace the schrodinger MCP tools. Do NOT use it to pick a free tool when a validated FEP+, WaterMap, IFD-MD, or Prime MM-GBSA result is actually required.
visual-review
Take screenshots of web pages and UI using Playwright for visual review and iteration
status
Diagnostic status report — shows metaswarm installation state, project setup, and potential issues
start
Use when starting work on any task, when the user mentions metaswarm, or when the user wants to begin tracked development work
setup
Interactive project setup — detects your project, configures metaswarm, writes project-local files