Browse generation models filtered by category: image, video, or audio.
MIT
650,501 tools. Updated 2026-10-13 23:30
"Using Hugging Face for Text-to-Audio, Image, and Video Generation" matching MCP tools:
- Search for Hugging Face models by keyword or task. Find models for text classification, summarization, image generation, and more.MIT
- Retrieve currently trending models on Hugging Face by live trending score. Filter by task (e.g., text-generation) and adjust result count up to 50.MIT
- Generate videos from text prompts, images, or audio using AI models like p-video, wan, and vace. Supports custom durations, resolutions, and aspect ratios.MIT
- Retrieve available image, video, and audio generation models with their type and pricing information for selection.MIT
- Discover trending AI models from Hugging Face to identify popular tools for tasks like text-generation or image-classification.MIT
Matching MCP Servers
- AlicenseBqualityDmaintenanceEnables image and video generation using BigModel AI's CogView and CogVideoX models via MCP, supporting batch image generation and various configuration options.619 npm4MIT
- AlicenseBqualityDmaintenanceEnables downloading videos from platforms like YouTube and converting them to text using OpenAI Whisper and ffmpeg. It supports multiple output formats including TXT, JSON, SRT, and VTT for transcriptions.12212 npmISC
Matching MCP Connectors
Transcribe audio and video files to text, SRT and VTT subtitles in 99 languages with Whisper.
Transcribe TikTok, Instagram Reels, X, Facebook and MP4 videos to text with Whisper.
- Create a talking-head video by combining a face image with WAV audio. Provide image_url and audio_url to generate speech-driven video.MIT
- Create a lipsync video from an audio track or script paired with a still image or video. Use a voice ID to make the visual say the provided text.MIT
- Detect faces in an image or video to get face coordinates for multi-face swaps. Use the returned task ID to retrieve detected faces before swapping.Apache 2.0
- Uploads user-provided image, video, or audio to Sync asset storage and returns a durable assetId for use in subsequent lipsync generation.MIT
- Swap faces in a video using an uploaded face image. Automate video face swap for apps, pipelines, or batch processing.Apache 2.0
- Convert a script or subject into spoken WAV audio using system TTS or an optional Hugging Face model, returning the file path and exact duration.MIT
- Generate a JSON configuration for video generation with support for clips, layers, transitions, and audio options, ready for validation or API submission.MIT
- Upload a local image, video, or audio file to obtain a public HTTPS URL for use in video generation tasks, avoiding base64 truncation issues.MIT
- Queue video generation using AI models like Veo 3.1, Kling, Wan, and more. Supports text, image, video, and audio inputs with NSFW prompts.MIT
- Generate a video from a text prompt or a start image URL. Returns request ID and cost instantly; video renders in 1-10 minutes.MIT
- Generate a lipsync video by providing visual and audio inputs (URL or assetId) and receive a generation ID to track and retrieve the result.MIT
- Generate AI images or videos asynchronously by submitting a task and polling for the result. Supports text-to-image, image-to-video, reference-to-video, and video editing models.MIT
- List all element types a Zvid project supports, including visuals (IMAGE, VIDEO, GIF, SVG, TEXT), AUDIO, SUBTITLE, and SCENE, with summaries and required fields.MIT
- Get documentation for any element type: required fields, supported fields with constraints, gotchas, and a valid example. Supports IMAGE, VIDEO, GIF, SVG, TEXT, AUDIO, SUBTITLE, SCENE.MIT
- 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