List Workspaces and Projects

List workspaces, projects, versions, and trained models using the REST API, Python SDK, and CLI.

About

The workspace endpoint returns metadata about a workspace and every project it contains - including each project's type, image and annotation counts, versions, and dataset splits. Use it to enumerate the projects your API key can access (for example, to discover project IDs before uploading data or exporting a version) and to drill into a project's generated versions, trained models, and dataset exports. The same data is available through the REST API, the Python SDK, and the CLI.

HTTP API

The /:workspace endpoint gives you information about your workspace and its Projects. This endpoint lists all Projects in the Workspace your API key authenticates against, and you can dive deeper into any project to find information about its generated versions, models, and dataset exports.

The endpoint URL is:

curl "https://api.roboflow.com/roboflow?api_key=$ROBOFLOW_API_KEY"

Here is an example of a response from the endpoint:

{
    "workspace": {
        "name": "Roboflow",
        "url": "roboflow",
        "members": 7,
        "projects": [
            {
                "id": "roboflow/chess-sample-4ckfl",
                "type": "object-detection",
                "name": "Chess Sample",
                "created": 1630335544.592,
                "updated": 1630335741.988,
                "images": 12,
                "unannotated": 3,
                "annotation": "pieces",
                "versions": 3,
                "public": false,
                "splits": {
                    "train": 9,
                    "test": 1,
                    "valid": 2
                },
                "classes": {
                    "white-queen": 7,
                    "black-queen": 4,
                    "black-bishop": 8,
                    "white-knight": 10,
                    "white-bishop": 11,
                    "black-knight": 11,
                    "black-rook": 10,
                    "white-pawn": 34,
                    "black-pawn": 37,
                    "white-rook": 10,
                    "black-king": 8,
                    "white-king": 8
                }
            }
        ]
    }
}

Get a Project and List Versions

You can retrieve information about a project using the following REST endpoint:

curl "https://api.roboflow.com/roboflow/chess-sample-4ckfl?api_key=$ROBOFLOW_API_KEY"

This endpoint returns a JSON response with the following structure:

{
    "workspace": {
        "name": "Roboflow",
        "url": "roboflow",
        "members": 7
    },
    "project": {
        "id": "roboflow/chess-sample-4ckfl",
        "type": "object-detection",
        "name": "Chess Sample",
        "created": 1630335544.592,
        "updated": 1630335741.988,
        "images": 12,
        "unannotated": 3,
        "annotation": "pieces",
        "public": false,
        "splits": {
            "valid": 2,
            "train": 9,
            "test": 1
        },
        "classes": {
            "white-queen": 7,
            "white-king": 8,
            "black-knight": 11,
            "black-pawn": 37,
            "black-rook": 10,
            "white-pawn": 34,
            "black-bishop": 8,
            "white-knight": 10,
            "black-queen": 4,
            "white-bishop": 11,
            "black-king": 8,
            "white-rook": 10
        },
        "versions": [
            {
                "id": "roboflow/chess-sample-4ckfl/3",
                "name": "raw",
                "created": 1630335741.989,
                "images": 12,
                "splits": {
                    "train": 9,
                    "test": 1,
                    "valid": 2
                },
                "preprocessing": {
                    "auto-orient": {
                        "enabled": true
                    }
                },
                "augmentation": {},
                "exports": [
                    "coco",
                    "voc"
                ]
            },
            {
                "id": "roboflow/chess-sample-4ckfl/2",
                "name": "416x416",
                "created": 1630335730.142,
                "images": 12,
                "splits": {
                    "train": 9,
                    "test": 1,
                    "valid": 2
                },
                "preprocessing": {
                    "resize": {
                        "enabled": true,
                        "format": "Stretch to",
                        "width": 416,
                        "height": 416
                    },
                    "auto-orient": {
                        "enabled": true
                    }
                },
                "augmentation": {},
                "exports": []
            },
            {
                "id": "roboflow/chess-sample-4ckfl/1",
                "name": "augmented",
                "created": 1630335698.746,
                "images": 30,
                "splits": {
                    "valid": 2,
                    "train": 27,
                    "test": 1
                },
                "model": {
                    "id": "chess-sample-4ckfl/1",
                    "endpoint": "https://serverless.roboflow.com/infer/chess-sample-4ckfl/1",
                    "start": 1630335799.682,
                    "end": 1630337523.889,
                    "fromScratch": false,
                    "tfjs": true,
                    "oak": true,
                    "map": "62.87",
                    "recall": "85.29",
                    "precision": "23.44"
                },
                "preprocessing": {
                    "resize": {
                        "enabled": true,
                        "width": 416,
                        "format": "Stretch to",
                        "height": 416
                    },
                    "auto-orient": {
                        "enabled": true
                    },
                    "grayscale": {
                        "enabled": true
                    }
                },
                "augmentation": {
                    "exposure": {
                        "percent": "25",
                        "enabled": true
                    },
                    "brightness": {
                        "percent": "25",
                        "enabled": true,
                        "darken": true,
                        "brighten": true
                    },
                    "rotate": {
                        "degrees": "5",
                        "enabled": true
                    },
                    "image": {
                        "enabled": true,
                        "versions": "3"
                    },
                    "flip": {
                        "enabled": true,
                        "horizontal": true,
                        "vertical": false
                    },
                    "crop": {
                        "min": 0,
                        "percent": 30,
                        "enabled": true
                    },
                    "noise": {
                        "percent": "2",
                        "enabled": true
                    }
                },
                "exports": [
                    "yolov5pytorch"
                ],
                "versionNotes": "Fix: rotated box misalignment"
            }
        ]
    }
}

List Project Models

You can retrieve all trained models in a project using the /:workspace/:project/models endpoint. This returns both version-trained models and standalone models (such as NAS children).

With Sign In With Roboflow (Getting Started), use Authorization: Bearer and scope model:infer instead of api_key:

curl -H "Authorization: Bearer $ACCESS_TOKEN" \
  "https://api.roboflow.com/:workspace/:project/models"

List All Models

curl "https://api.roboflow.com/:workspace/:project/models?api_key=$ROBOFLOW_API_KEY"

Filter by NAS Group

To list only the models from a specific NAS run, pass the group query parameter:

curl "https://api.roboflow.com/:workspace/:project/models?group=GROUP_ID&api_key=$ROBOFLOW_API_KEY"

The group value is the NAS run identifier returned on each model object. If the group doesn't match any models, the endpoint returns an empty array.

Response

The endpoint returns a JSON array of model objects:

[
  {
    "url": "my-workspace/my-project/3",
    "version": "3",
    "train": { "status": "finished" },
    "modelType": "rfdetr-base",
    "name": "My Model",
    "created": "2026-04-01T00:00:00.000Z",
    "metrics": {
      "map50": 91.0,
      "precision": 88.0,
      "recall": 85.0
    }
  }
]

NAS Model Fields

Models produced by Neural Architecture Search include additional fields:

{
  "url": "my-workspace/my-project-410-nas-gpu-066866",
  "train": { "status": "finished" },
  "modelType": "rfdetr-nas-S",
  "name": "NAS Child 1",
  "created": "2026-04-01T00:00:00.000Z",
  "nasFamily": "child",
  "group": "pVYKOWUB6AUIVJMgPc7u-410-rfdetrNasGroup",
  "favorites": {},
  "recommended": true,
  "metrics": {
    "map50": 81.2,
    "map5095": 64.3,
    "f1": 78.0,
    "hardware": "gpu",
    "latency": 1.157,
    "paretoOptimalFor": ["gpu"]
  }
}

Field	Type	Description
nasFamily	string	"child" for NAS-discovered models, null for the baseline
group	string	NAS run identifier, shared by all models in the same run
favorites	object	Map of user IDs to favorite status
recommended	boolean	Present and true when this model is the recommended pick for at least one metric/hardware combination
metrics.map5095	number	mAP@50-95 score (percentage)
metrics.f1	number	F1 score (percentage)
metrics.hardware	string	Hardware target the model was benchmarked on (e.g. "gpu", "jetson-orin-nano")
metrics.latency	number	Inference latency in milliseconds on the target hardware
metrics.paretoOptimalFor	string[]	Hardware targets for which this model sits on the Pareto frontier

These fields are only present on NAS models. Standard trained models are not affected.

Python SDK

Get a Workspace handle for the workspace your API key authenticates against:

import roboflow

rf = roboflow.Roboflow(api_key="YOUR_API_KEY")
workspace = rf.workspace()

Each Roboflow API key is scoped to a single workspace. To work against a different workspace, use a different API key (or, for public Universe workspaces, pass the workspace slug):

# Public Universe workspace - only your API key is needed.
public_ws = rf.workspace("roboflow-100")

Workspace properties

The returned Workspace exposes:

• workspace.url - the workspace's URL slug (e.g. my-workspace).

• workspace.name - the workspace's display name.

• workspace.list_projects() - projects in the workspace, as a list of dicts.

• workspace.projects() - same data as list_projects() but returned as a Project object list (older alias).

• workspace.list_folders() - see Manage Folders.

• workspace.list_workflows() - see Manage Workflows.

• workspace.get_plan() and workspace.get_usage() - see Workspace Plan and Usage.

List Projects and Versions

List Projects

Get the projects in your workspace:

import roboflow

rf = roboflow.Roboflow(api_key="YOUR_API_KEY")
workspace = rf.workspace()

for project in workspace.list_projects():
    print(project["id"], project["name"], project["type"])

Each entry includes the project's id (URL slug), display name, project type, image count, and a few other metadata fields.

To work against a public Universe workspace, pass its slug:

universe_ws = rf.workspace("roboflow-100")

Get a Project

project = workspace.project("my-detector")

Or use the top-level shortcut:

project = rf.project("my-detector")

List Versions

for version in project.versions():
    print(version.version, version.name)

project.versions() returns Version objects you can call methods on directly (download, train, delete, etc.). For a lightweight dict response, use project.list_versions() or project.get_version_information().

Get a Version

version = project.version(3)

Numeric - versions are 1-indexed.

CLI

List Workspaces

You can retrieve a list of all Workspaces of which you are a member with the CLI.

To list Workspaces with the CLI, use the following command:

roboflow workspace list

This will return a list of Workspaces with their corresponding application links and Workspace IDs:

NAME             ID               DEFAULT
My Workspace     my-workspace     *
Other Workspace  other-ws

To get the output as JSON (for use in scripts or AI agents):

roboflow workspace list --json

[
  {"name": "My Workspace", "url": "my-workspace", "link": "https://app.roboflow.com/my-workspace", "default": true},
  {"name": "Other Workspace", "url": "other-ws", "link": "https://app.roboflow.com/other-ws", "default": false}
]

List Projects in a Workspace

To list projects in a workspace, use the following command:

roboflow project list

If you have a default workspace configured, the -w flag is optional. Otherwise, specify it:

roboflow project list -w WORKSPACE_ID

This will return a table of Projects:

NAME              ID                              TYPE                VERSIONS  IMAGES
my-dataset        my-workspace/my-dataset         object-detection    3         500
classifier        my-workspace/classifier         classification      1         200

To get the output as JSON:

roboflow project list --json

Get a Project

To get detailed information about a project, use the following command:

roboflow project get PROJECT_ID

You can use the resource shorthand - no need to specify the workspace separately:

roboflow project get my-dataset              # uses default workspace
roboflow project get my-workspace/my-dataset  # explicit workspace

This will return information about the project including its versions:

Project: my-dataset
  ID: my-workspace/my-dataset
  Type: object-detection
  Images: 500
  Versions: 3
  Classes: car (200), truck (150), bus (150)
  Link: https://app.roboflow.com/my-workspace/my-dataset

To get the full JSON response:

roboflow project get my-dataset --json

MCP Server

Connect your AI agent to the MCP Server and it can list what is in your workspace with these tools:

Tool	Description
projects_list	List projects in the workspace.
projects_get	Get project detail including versions, classes, splits, and trained models.