Protocol-level facts for Roboflow REST and Inference APIs — URL patterns, auth, parameters, error codes, and SDK quick-start. For deployment strategy and Workflow execution patterns, see roboflow-inference.
78
71%
Does it follow best practices?
Impact
84%
1.15xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
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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.
| 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.
| 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.
| 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 |
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")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()| 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/inference/workflows ("Video Stream" section). Not a plain HTTP call. |
roboflow://skills/api-reference/inference — inference URL patterns, request/response formatsroboflow://skills/api-reference/rest-api — platform REST API endpoints (CRUD, upload, training)02936d5
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