Roboflow Universe

> For agents — source-of-truth: This skill is authored in roboflow/computer-vision-skills and shipped with the Roboflow plugin. If your client has loaded the plugin (you'll see roboflow: skills in your available skills list), use those local skills — they're read fresh from disk every session. The same content served as MCP resources at roboflow://skills//... is a fallback for clients without the plugin and may lag this repo. Don't call ReadMcpResourceTool for roboflow://skills/... URIs when a local roboflow: skill is available.

Roboflow Universe

Open repository of 1M+ computer vision datasets and 50K+ pre-trained models at universe.roboflow.com.

URL Patterns

| Page | URL | Content | |------|-----|---------| | Home | universe.roboflow.com | Search, trending projects, categories | | Project | universe.roboflow.com/{owner}/{project} | Overview, classes, metrics, license, fork | | Images | universe.roboflow.com/{owner}/{project}/browse | Browse images with annotations | | Dataset version | universe.roboflow.com/{owner}/{project}/dataset/{version} | Version details, splits, download | | Model | universe.roboflow.com/{owner}/{project}/model/{version} | Try model, metrics, deploy snippet |

Searching Universe

MCP app (universe_search_app)

Use when someone must choose a dataset after seeing it: previews, classes, license, image counts, etc. Pure MCP JSON hits from universe_search are not a substitute for that UX — open the app when the decision needs eyes on the listings.

MCP Tool

Use universe_search to find datasets/models programmatically. Pass a descriptive query (e.g. "hard hat detection construction site").

Web Search

Search is hybrid — combines semantic similarity with keyword matching. Use specific, descriptive queries for best results.

Query Operators

All operators can be mixed with free-text: fire smoke class:fire,smoke images>200 model

| Operator | Example | Effect | |----------|---------|--------| | model | waste detection model | Only datasets with a trained model | | object detection | helmet object detection | Filter by project type (also: classification, instance segmentation, keypoint detection) | | class:X | class:helmet,person | Must contain these classes | | tag:X | tag:safety | Filter by Universe tag | | model:X | model:yolov8 | Filter by trained model architecture | | images>N | images>500 | Min image count (also >=, =N | stars>=5 | Min star count | | views>N | views>1000 | Min view count | | downloads>N | downloads>100 | Min download count | | updated:Nd | updated:30d | Updated within N days (also h, w, mo, y) | | sort:X | sort:stars | Sort by field (stars, images, updated, downloads, views) | | like:dataset-url | like:coco | Find similar datasets |

Tips for Effective Queries

• Combine free-text with operators: pothole road damage class:pothole images>100 sort:stars
• Add model to only get inference-ready datasets
• Include project type keywords to filter: helmet instance segmentation
• Use class: when you know exactly what classes you need
• Use specific object names, not generic terms ("forklift in warehouse" > "vehicle")

Evaluating a Dataset

Before forking, check these signals:

| Criterion | Where to Look | Good Sign | |-----------|---------------|-----------| | Class coverage | Classes list on project page | All your target classes present | | Image count | Project overview | 500+ images per class for detection | | Annotation quality | Browse > click individual images | Tight bounding boxes, consistent labels | | Class balance | Project overview / health | No extreme class imbalance | | Image diversity | Browse images | Varied lighting, angles, backgrounds | | License | "Cite this Project" section | Compatible with your use case (see below) | | Model metrics | Model tab (if available) | mAP > 70% suggests decent annotations |

Licenses

Found in the "Cite this Project" section on the project page. No license listed = all rights reserved.

| License | Commercial Use | Modify | Attribution Required | |---------|---------------|--------|---------------------| | Public Domain | Yes | Yes | No | | CC BY 4.0 | Yes | Yes | Yes | | MIT | Yes | Yes | Yes (in license copy) | | BY-NC-SA 4.0 | No | Yes (share-alike) | Yes | | ODbL v1.0 | Yes | Yes (share-alike for DB) | Yes | | No license specified | Assume No | Assume No | N/A |

Forking a Dataset

Fork = copy a Universe dataset into your workspace (no download/re-upload needed).

1. Open dataset on Universe
2. Click Download Dataset button
3. Choose Train a model with this dataset (full fork) or Train from a portion of this dataset (partial clone)
4. Dataset copies into your workspace

After forking you can: rename classes, add/remove images, generate versions, train models.

Requires: Logged-in Roboflow account.

Downloading a Dataset

For local/notebook training instead of Roboflow cloud training.

| Method | When to Use | |--------|-------------| | Train a model with this dataset (fork) | Training on Roboflow, want full data in workspace | | Train from a portion (clone) | Want a subset or to combine with other data | | Download dataset | Local training via code snippet or ZIP file |

Supports all standard export formats (COCO, YOLO, VOC, CreateML, TFRecord, etc.).

Path: Project page > Download Dataset button > choose method.

Using a Universe Model

Direct Inference via Workflows

1. Create a Workflow in Roboflow
2. Add a model block
3. Switch to Public Models tab
4. Paste the model ID from the Universe model page (copy icon at top)
5. Click Use model ID

Model ID format: {owner}/{project}/{version} (shown on Universe model page).

Checkpoint Training

Fork the dataset, then train your own model using the forked data. Use a Universe model's architecture as a starting point via Roboflow Train.

Inference Metrics (shown on model page)

| Project Type | Metrics Shown | |--------------|---------------| | Object Detection | mAP, precision, recall | | Classification | Accuracy | | Segmentation | mAP, precision, recall |

MCP Tool Reference

universe_search — Search Universe for datasets/models.

| Param | Type | Default | Notes | |-------|------|---------|-------| | query | str (required) | — | Search query text | | result_type | "dataset" \| "model" \| null | null | Filter by result type | | limit | int | 12 | Max results per page | | page | int | 1 | Page number (1-indexed) |

Returns: name, url, type, classes, classCount, images, description, tags, license, stars, views, downloads, modelCount, latestVersion.

Related Skills

• roboflow://skills/data-management/SKILL — managing datasets after import
• roboflow://skills/training-and-evaluation/SKILL — training on forked data

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: roboflow
• Source: roboflow/computer-vision-skills
• License: Apache-2.0

Install and usage instructions live in the source repository linked above.