Search and filter public datasets on Ultralytics Explore by query, task, and sort order. Find relevant datasets for your computer vision projects.
MIT
458,064 tools. Updated 2026-08-14 22:15
"Ultralytics" matching MCP tools:
- Retrieve a list of computer-vision projects from your Ultralytics workspace. Specify username to filter.MIT
- Search public projects on Ultralytics Explore by providing a query, with options to sort results and paginate using an offset.MIT
- Create a new project in the Ultralytics workspace to organize models, datasets, and training runs.MIT
- List datasets in your Ultralytics workspace by providing a username.MIT
- Need a new dataset for your project? Create one in your Ultralytics workspace by providing name, slug, task, class names, visibility, and description.MIT
Matching MCP Servers
- AlicenseBqualityAmaintenanceEnables management and interaction with the Ultralytics Platform, including browsing projects/datasets/models, starting training, running predictions, and creating exports.28369MIT
- Flicense-qualityDmaintenanceA Model Context Protocol compliant server that provides RESTful API access to Ultralytics YOLO operations for computer vision tasks including training, validation, prediction, export, tracking, and benchmarking.4
- Retrieve real-time cloud GPU stock status by GPU type to identify available GPU resources for training.MIT
- Retrieve detailed information for a specific dataset using its ID, slug, username/slug, or ul:// URI.MIT
- List models in a project using its ID, slug, username/slug, or ul:// URI.MIT
- Remove a project from the Ultralytics Platform using its id, slug, or URI. Soft-delete preserves data for recovery.MIT
- Delete a model from the Ultralytics Platform using its ID or, for slug-based deletion, by providing the project reference.MIT
- Retrieve detailed information for a specific project using its id, slug, username/slug, or ul:// URI.MIT
- Check the status of an export job by providing its unique 24-character export ID.MIT
- Get a model by its unique ID, or by slug when combined with a project reference.MIT
- Start a cloud training job using an existing model or official YOLO checkpoint. Requires cost confirmation to proceed.MIT
- Run inference with a trained model on images provided via URL or base64 string to generate predictions.MIT
- List export jobs for a model by specifying the model ID or slug.MIT
- Get export links for datasets on the Ultralytics Platform. Specify a dataset reference and optionally a version to obtain the export URL.MIT
- Report a model's training status and progress for private and public projects. Access metrics and history to track performance.MIT
- Soft-delete a dataset from the Ultralytics Platform using its id, slug, or URI to remove it from active projects.MIT