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741,519 tools. Updated 2026-11-04 05:16

"Exploring text-to-image generation techniques" matching MCP tools:

  • Identify which media generation capabilities are available, such as text-to-image, image-to-video, lipsync, and text-to-speech. Use this overview to choose a mode and continue.
    MIT
  • List every available video generation model, its capabilities (text-to-video, image-to-video, audio), supported durations, and whether it is available via the API. Call this to retrieve available model ids before calling generate_video.
    MIT
  • Generate images from text prompts using ModelScope AI models. Supports text-to-image and image-to-image, with an optional source image for transformation.
    Apache 2.0
  • Identify images on a web page and queue alt-text generation jobs. Uses account credits; processed asynchronously, with results available in the image library.
    MIT
    Destructive
  • Request a five-minute, no-charge quote for text-to-3D or single-image 3D generation; it saves the input for creating a job.
    MIT
  • Search for AI workflows by name, description, or keywords to find tools for image generation, text processing, and more.
    MIT

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  • OCR text from image URLs, 30 languages, lines with boxes. One flat row per image. Billed on text.

  • Extract text from PNG, JPEG, TIFF, WebP, BMP and GIF images with OCR in 27 languages.

  • Start OfflineCreator Studio jobs from prompts: queue text-to-image or text-to-video, and for image-to-video upload input after reserving; set wait to poll until completed or failed.
    MIT
  • Generate 3D models from text prompts or image URLs by submitting a generation job, returning a task ID for tracking.
    MIT
  • Upload a source image for a reserved image-to-video generation and start processing. Provide a local path inside the upload root or base64 data.
    MIT
  • Search for Hugging Face models by keyword or task. Find models for text classification, summarization, image generation, and more.
    MIT
  • Generate videos from text prompts or images using Google Veo models. Starts a background generation process and returns a session ID to track progress.
    MIT
  • Create one AI image from a text prompt or reference image for sprites, flipbooks, emissive/UI textures, or concept art; returns a generation ID to poll.
    MIT
  • Check image generation or editing task status and retrieve resulting image URLs and metadata. Use to monitor completion and access outputs from previous requests.
    MIT
  • Queue AI video/image generation in Symphony with modes for reference, image, text, or image-to-image. Check cost with a dry-run, then render and retrieve results via wait.
    MIT