roboflow/computer-vision-skills

roboflow-api-reference

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.

First seen May 5, 2026

Installation

$ npx skills add roboflow/computer-vision-skills --skill roboflow-api-reference

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from roboflow/computer-vision-skills.

npx skills add roboflow/computer-vision-skills

Browse all from roboflow/computer-vision-skills

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 35
License LICENSE
Default branch main
Open issues 1
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,710 B
  • docs SUMMARY.md 238 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 236 installs

SKILL.md

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 ?apikey=YOURKEY
Request body Platform API + Workflow inference "apikey": "YOURKEY" 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.