fal.ai Image Generation Server
MCP fal.ai Image Server Effortlessly generate images from text prompts using fal.ai and the Model Context Protocol (MCP). Integrates directly with AI IDEs like Cursor and Windsurf. ## When and Why to Use This tool is designed for: - Developers and designers who want to generate images from text prompts without leaving their IDE. - Rapid prototyping of UI concepts, marketing assets, or creative ideas. - Content creators needing unique visuals for blogs, presentations, or social media. - AI researchers and tinkerers experimenting with the latest fal.ai models. - Automating workflows that require programmatic image generation via MCP. Key features: - Supports any valid fal.ai model and all major image parameters. - Works out of the box with Node.js and a fal.ai API key. - Saves images locally with accessible file paths. - Simple configuration and robust error handling. ## Quick Start 1. Requirements: Node.js 18+, fal.ai API key 2. Configure MCP: { "mcpServers": { "fal-ai-image": { "command": "npx", "args": ["-y", "mcp-fal-ai-image"], "env": { "FAL_KEY": "YOUR-FAL-AI-API-KEY" } } } } 3. Run: Use the generate-image tool from your IDE. 💡 Typical Workflow: Describe the image you want (e.g., “generate a landscape with flying cars using model fal-ai/kolors, 2 images, landscape_16_9”) and get instant results in your IDE. ### 🗨️ Example Prompts - generate an image of a red apple - generate an image of a red apple using model fal-ai/kolors - generate 3 images of a glowing red apple in a futuristic city using model fal-ai/recraft-v3, square_hd, 40 inference steps, guidance scale 4.0, safety checker on Supported parameters: prompt, model ID (any fal.ai model), number of images, image size, inference steps, guidance scale, safety checker. Images are saved locally; file paths are shown in the response. For model IDs, see fal.ai/models. ## Troubleshooting - FAL_KEY environment variable is not set: Set your fal.ai API key as above. - npx not found: Install Node.js 18+ and npm. Advanced: Example MCP Request/Response Request: { "tool": "generate-image", "args": { "prompt": "A futuristic cityscape at sunset", "model": "fal-ai/kolors" } } Example response: { "images": [ { "url": "file:///path/to/generated_image1.png" }, { "url": "file:///path/to/generated_image2.png" } ] } ## 📁 Image Output Directory Generated images are saved to your local system: - By default: ~/Downloads/fal_ai (on Linux/macOS; uses XDG standard if available) - Custom location: Set the environment variable FAL_IMAGES_OUTPUT_DIR to your desired folder. Images will be saved in /fal_ai. The full file path for each image is included in the tool's response. ## ⚠️ Error Handling & Troubleshooting - If you specify a model ID that is not supported by fal.ai, you will receive an error from the backend. Double-check for typos or visit fal.ai/models to confirm the model ID. - For the latest list of models and their capabilities, refer to the fal.ai model catalog or API docs. - For other errors, consult your MCP client logs or open an issue on GitHub. ## 🤝 Contributing Contributions and suggestions are welcome! Please open issues or pull requests on GitHub. ## 🔒 Security - Your API key is only used locally to authenticate with fal.ai. - No user data is stored or transmitted except as required by fal.ai API. ## 🛡 License MIT License © 2025 Madhusudan Kulkarni
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-02.
Scan details: Circle-IR · 2026-09-02 · Appeal
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- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- container
- Category
- version-control
- Source
- Smithery
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve fal.ai Image Generation Server from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp --scope user for --scope project to commit it to .mcp.json.