The generative media platform for developers with 600+ AI models for image, video, voice, and audio generation
Tool to cancel a queued or in-progress request in fal.ai's queue system. Use when you need to stop a request before it completes. Note that cancellation only succeeds if the request hasn't started processing; if already completed, returns an error status. Even with successful cancellation, the request may still execute if it was near the front of the queue.
Tool to check the status of a queued request in fal.ai. Use when you need to monitor the progress of an async request. Returns different information based on status: queue position when IN_QUEUE, logs when IN_PROGRESS or COMPLETED.
Tool to estimate pricing for fal.ai model endpoints. Use when you need to calculate expected costs for API calls or unit-based usage across one or more endpoints.
Tool to retrieve public keys for webhook signature verification. Returns a JSON Web Key Set containing ED25519 public keys. Use when you need to verify webhook signatures from fal.ai. The keys are cacheable but should be refreshed at least every 24 hours.
Tool to retrieve unit pricing for model endpoints. Returns pricing information including unit price, billing unit, and currency. Use when you need to check costs for specific fal.ai models.
Tool to discover and search fal.ai model endpoints. Use when you need to list all models, find specific models by ID, or search by category/query. Supports pagination and optional expansion of OpenAPI schemas.
Tool to retrieve the final result of a completed queue request. Use when you need to get the output of a model request that was submitted to the queue and has finished processing. Only works after request status transitions to COMPLETED.
Tool to invoke a fal.ai model synchronously via fal.run, generating new content (images, audio, video, or other model outputs) hosted at fal.ai CDN URLs in the response. Each call executes paid inference on fal.ai — it consumes the connected account's credit balance and is billed per request, so it is NOT a read-only operation. Use when you need a single-shot result and the model is fast enough to return inline — the request blocks until the model finishes and returns the generated output directly. For long-running jobs, parallel invocations, or anything production-grade, prefer SUBMIT_ASYNC_JOB (queue.fal.run) which adds persistence, retries, and webhooks; both produce the same kind of newly-generated, persistently-hosted output and are billed identically.
Tool to stream request status updates via SSE. Use when you need real-time updates on a queued request's processing state.
Tool to submit an asynchronous inference job to fal.ai's queue (queue.fal.run). Use when you want to run a model without blocking — fal.ai persists the request, auto-scales runners, and you fetch the result later via the returned request_id (use QUEUE_GET_STATUS to poll, GET_QUEUE_REQUEST_RESULT to retrieve, CANCEL_QUEUE_REQUEST to abort, QUEUE_GET_STATUS_STREAM to receive SSE updates). Supports an optional webhook_url that fal.ai will POST results to on completion.
Tool to submit a fal.ai inference job to the async queue and block until it completes (or a deadline is reached), returning the model's final result. Mirrors fal-js's `subscribe()` ergonomics: SUBMIT_ASYNC_JOB + QUEUE_GET_STATUS polling + GET_QUEUE_REQUEST_RESULT in one call. Use when you want async-style reliability (queue persistence, retries) but a synchronous-style return value, and the model is fast enough to finish within max_wait_seconds. For very long jobs, prefer SUBMIT_ASYNC_JOB and check status/result manually or via webhook.
Tool to upload an input media file (image, audio, or video) to fal.ai's CDN and return a public access_url that can be passed as a model input. Many fal.ai models accept a URL for inputs like 'image_url', 'audio_url', or 'video_url' — use this action first to host the file, then pass the access_url to RUN_MODEL_SYNC or SUBMIT_ASYNC_JOB. Internally this performs fal.ai's two-step upload: (1) POST to rest.fal.ai/storage/upload/initiate to get a presigned upload URL, (2) PUT the bytes to that URL.