SuperAPI AI Directory

roboflow-api-reference

Coding & development

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Updated 10-15 22:10

About this skill

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:<name> 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/<name>/... 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:<name> skill is available.

Tip: If you're connected to the Roboflow MCP server, prefer its tools (projects_*, versions_*, models_*, workflows_*, images_*, …) over raw REST calls — they handle auth, pagination, and typed responses for you. The REST patterns below stay relevant if you're not using MCP.

Roboflow API Reference — Overview

API Hosts

Host Base URL Purpose
Platform API https://api.roboflow.com CRUD for projects, images, versions, training, upload
Serverless Inference https://serverless.roboflow.com Model inference + Workflow execution
Dedicated Deployment https://<name>.roboflow.cloud Private GPU inference (same API as serverless)
Self-hosted Inference http://localhost:9001 Local inference server via inference package

Use the inference-sdk Python package as the preferred client for all inference hosts. It handles auth, retries, and response parsing.

Authentication

Method Where Format
Query parameter All hosts ?api_key=YOUR_KEY
Request body Platform API + Workflow inference "api_key": "YOUR_KEY" in JSON body
Header MCP server (mcp.roboflow.com) x-api-key: YOUR_KEY (handled automatically by MCP)

API keys are workspace-scoped. Get yours from Workspace Settings > API Keys in the Roboflow dashboard (app.roboflow.com/{workspace}/settings/api). Personal API keys are at /settings/account → API Keys tab.

SDKs

SDK Install Primary Use
Python (inference-sdk) pip install inference-sdk Inference via InferenceHTTPClient
Python (roboflow) pip install roboflow Upload, training, project management
JavaScript (roboflow.js) Browser script tag Real-time on-device web inference
iOS (Swift) CocoaPods/SPM On-device mobile inference

Python inference-sdk Quick Start

from inference_sdk import InferenceHTTPClient

CLIENT = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",  # or dedicated URL, or localhost
    api_key="YOUR_KEY"
)
result = CLIENT.infer("image.jpg", model_id="your-project/1")

Python roboflow SDK Quick Start

import roboflow

rf = roboflow.Roboflow(api_key="YOUR_KEY")
project = rf.workspace("my-workspace").project("my-project")

# Upload
project.upload(image_path="image.jpg", split="train")

# Inference
model = project.version(1).model
result = model.predict("image.jpg", confidence=40).json()

Host Selection Guide

Task Host to Use
Run model inference serverless.roboflow.com
Run Workflows serverless.roboflow.com
Upload images api.roboflow.com
Manage projects/versions api.roboflow.com
Start training api.roboflow.com
High-throughput / SLA inference Dedicated deployment URL
Air-gapped / on-prem inference Self-hosted localhost:9001
Real-time video / webcam / RTSP WebRTC via inference_sdk.webrtc against serverless or local — see roboflow://skills/roboflow-inference/workflows ("Video Stream" section). Not a plain HTTP call.

Rate Limits

  • Serverless API: rate limits vary by plan
  • File upload max: 20 MB

Related Pages

  • roboflow://skills/roboflow-api-reference/inference — inference URL patterns, request/response formats
  • roboflow://skills/roboflow-api-reference/rest-api — platform REST API endpoints (CRUD, upload, training)
  • roboflow://skills/roboflow-api-reference/api-key-management — creating and managing API keys via REST, MCP tools, and Python CLI. When creating a key, scope it to least privilege if the workspace has Advanced API Keys; if not, tell the user scoped keys are an Enterprise feature.