Search for Hugging Face models by keyword or task. Find models for text classification, summarization, image generation, and more.
MIT
457,697 tools. Updated 2026-08-14 14:35
"Using Hugging Face for Text-to-Audio, Image, and Video Generation" matching MCP tools:
- 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
- Browse generation models filtered by category: image, video, or audio.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.6534MIT
- 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.213ISC
Matching MCP Connectors
Generate images & video (Nano Banana, Veo, Omni) pay-as-you-go. No subscription, crypto payments.
Connect to Hugging Face Hub and thousands of Gradio AI Applications
- Search for specific text within Hugging Face datasets to find relevant data entries for analysis or training.MIT
- Retrieve the complete JSON schema for video generation to understand all configuration options, constraints, and examples before creating valid video configurations.MIT
- Generate a JSON configuration for video generation with support for clips, layers, transitions, and audio options, ready for validation or API submission.MIT
- Explore video generation models with detailed specs: modes, aspect ratios, durations, resolutions, media inputs, audio support, strengths, and pricing. Use to select the right model or verify parameters before generation.Apache 2.0
- Diagnose SuperCMO setup by checking which media-generation keys are set and which capabilities (image, video, audio) are ready. Use first when setting up or after a 'no_provider_configured' error.Apache 2.0
- 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
- Open the Sync upload widget to choose a ChatGPT file or upload a local image/audio, converting it to a durable assetId for later processing.MIT
- Uploads user-provided image, video, or audio to Sync asset storage and returns a durable assetId for use in subsequent lipsync generation.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