MCP server for fal.ai - Run 600+ AI models for image, video, audio generation and more
If you already use Fal, the fal mcp server is the piece that lets your assistant work with it directly. MCP server for fal.ai - Run 600+ AI models for image, video, audio generation and more.
MCP (Model Context Protocol) server for fal.ai — access 600+ AI models for image generation, video creation, speech-to-text, text-to-speech, music generation, and more directly from Claude.
The toolset is worth reading before you wire it up, because it tells you what the integration is really for:
generate_image — Text-to-image generation (FLUX, Recraft, etc.)edit_image — Image editing, inpainting, upscalinggenerate_video — Text/image-to-video (Kling, Veo, Sora, LTX)speech_to_text — Audio transcription with Whispertext_to_speech — Text-to-speech synthesisgenerate_music — Music generation from text promptssearch_models — Search for available models on fal.airun_model — Run any fal.ai model with custom parametersInstallation goes through your MCP client rather than a global install: point it at fal-ai-mcp on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
Configuration is passed through the environment: FAL_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Fal's toolset — generate_image, edit_image, generate_video and 5 more — is a fair guide to whether it matches your workflow. It is maintained by enescanguven; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| generate_image | Text-to-image generation (FLUX, Recraft, etc.) |
| edit_image | Image editing, inpainting, upscaling |
| generate_video | Text/image-to-video (Kling, Veo, Sora, LTX) |
| speech_to_text | Audio transcription with Whisper |
| text_to_speech | Text-to-speech synthesis |
| generate_music | Music generation from text prompts |
| search_models | Search for available models on fal.ai |
| run_model | Run any fal.ai model with custom parameters |
{
"mcpServers": {
"fal-ai": {
"command": "npx",
"args": ["-y", "fal-ai-mcp"],
"env": {
"FAL_KEY": "your-fal-api-key"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| FAL_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.