fal.ai
This MCP server provides comprehensive access to fal.ai's AI model ecosystem, enabling AI assistants to discover, execute, and manage generative AI workflows through a unified interface. Built using Python with FastMCP, httpx for async HTTP operations, and support for both direct and queued model execution, it offers tools for browsing available models with pagination and search, retrieving OpenAPI schemas for model parameters, generating content with any fal.ai model including image generation and other AI tasks, and managing long-running requests through queue operations with status checking and cancellation. The implementation includes file upload capabilities to fal.ai's CDN storage, full streaming support via HTTP transport for real-time communication, and handles both authenticated operations requiring API keys and public model discovery, making it valuable for AI assistants that need access to cutting-edge generative models, automated content creation workflows, and scenarios requiring integration with fal.ai's specialized AI model marketplace.
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
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- media
- Source
- PulseMCP
- Repository
- github.com/derekalia/fal
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve fal.ai 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.