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MCP Sora demonstrates good definition quality with solid naming conventions, comprehensive descriptions, and well-structured schemas. All 8 tools follow verb_noun naming (sora_*) with clear action intent. Descriptions are generally 100-250 characters, within the 10-1024 baseline and informative about use cases. Input schemas are properly typed with enums and descriptions. However, output schemas are not documented, the tools return strings (raw text tables or JSON) without formal schema declarations. Error handling is minimal; there is no guidance on recovery paths or categorization. Tool compositions lack explicit dependencies or chaining hints.
Generate an AI video from a text prompt using Sora. This is the primary way to create videos - describe what you want and Sora will generate a video matching your description. Use this when: - You want to generate a video from a text description - You don't have reference images - You want creative AI-generated video content For image-to-video generation, use sora_generate_video_from_image instead. For character-based video generation, use sora_generate_video_with_character. Returns: Task ID and generated video information including URLs and state.
Generate an AI video asynchronously with callback notification. This is useful for long-running video generation tasks. Instead of waiting for the video to complete, you'll receive a callback at your specified URL when the generation is finished. Use this when: - You don't want to wait for the generation to complete - You have a webhook endpoint to receive results - You're integrating with an async workflow The callback will receive a POST request with the same response format as the synchronous generation tools. Returns: Task ID that you can use to correlate with the callback.
Generate an AI video from reference images using Sora (Image-to-Video). This allows you to animate or create videos based on provided images. The AI will use the images as visual references for the generated video. Use this when: - You have reference images you want to animate - You want the video to match a specific visual style - You want to bring static images to life Returns: Task ID and generated video information including URLs and state.
Output schemas not documented. Tools return free-form strings (text tables, JSON) without formal schema declarations. LLMs cannot plan downstream calls or reliably extract structured fields.
Error handling provides no recovery guidance. No error classification (retryable vs user-fixable vs fatal), no actionable error messages, and no suggestions for corrective action.
Async tool (sora_generate_video_async) lacks confirmation or dry-run pattern. Callback-based operations are irreversible, agents should confirm before committing to async generation with external webhook.
Inferred effective spec: 2026-07-28+.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | B | 78 | 2026-07-28+ | v2 |
Generate an AI video featuring a character from a reference video. This allows you to create new videos featuring a specific character extracted from another video. The character will be placed in the new scene described by the prompt. IMPORTANT: The reference video must NOT contain real people. Only animated or digital characters are supported. Use this when: - You want to reuse a character in different scenes - You're creating a series with the same character - You want consistent character appearance across videos Returns: Task ID and generated video information including URLs and state.
Query the status and result of a video generation task. Use this to check if a generation is complete and retrieve the resulting video URLs and metadata. Use this when: - You want to check if a generation has completed - You need to retrieve video URLs from a previous generation - You want to get the full details of a generated video Task states: - 'pending': Generation is still in progress - 'succeeded': Generation finished successfully - 'failed': Generation failed (check error message) Returns: Task status and generated video information including URLs and state.
Query multiple video generation tasks at once. Efficiently check the status of multiple tasks in a single request. More efficient than calling sora_get_task multiple times. Use this when: - You have multiple pending generations to check - You want to get status of several videos at once - You're tracking a batch of generations Returns: Status and video information for all queried tasks.
List all available Sora API actions and corresponding tools. Reference guide for what each action does and which tool to use. Helpful for understanding the full capabilities of the Sora MCP. Returns: Categorized list of all actions and their corresponding tools.
List all available Sora models and their capabilities. Shows all available model versions with their limits, features, and recommended use cases. Use this to understand which model to choose for your video generation. Returns: Table of all models with their version, limits, and features.
Tool composition hints missing. No explicit guidance on dependencies (e.g., 'Call sora_list_models first to choose a valid model enum'). Agents must infer chaining from descriptions alone.
Parameter constraint documentation incomplete. image_urls array has no min/max length; character_start/character_end have 0-1 range but no guidance on inclusive vs exclusive bounds; callback_url has no format validation hint.