brightdata-agent-onboarding（Brightdata Agent 加入）

Bright Data — Agent Onboarding

Bright Data gives agents reliable access to the open web: SERP results that look like a real browser, clean markdown from any URL (with CAPTCHA + JS handled), structured datasets for 40+ platforms (Amazon, LinkedIn, Instagram, TikTok, YouTube, Reddit, Crunchbase, …), and a Browser API for pages that need real interaction.

This skill is the entry point. Read it once, pick a path, then hand off to the narrower skill that owns that path.

Install

One command installs the CLI and the agent skills, and walks the human through OAuth in the browser:

# macOS / Linux — fastest install
curl -fsSL https://cli.brightdata.com/install.sh | bash

# Cross-platform (or if you don't want the install script)
npm install -g @brightdata/cli

# One-off, no install
npx --yes --package @brightdata/cli brightdata <command>

Requires Node.js >= 20. After install, both brightdata and bdata (shorthand) are available.

Then authenticate once:

bdata login

This single command:

1. Opens the browser for OAuth (or use bdata login --device on

headless / SSH machines)

1. Saves the API key locally — you never need to paste a token again
2. Auto-creates the required proxy zones (cli_unlocker,

cli_browser)

1. Sets sensible default configuration

For non-interactive setups you can pass the key directly:

bdata login --api-key <key>
# or
export BRIGHTDATA_API_KEY=<key>

Verify the install before doing real work:

bdata version
bdata config            # confirms auth + zones
bdata zones             # should list cli_unlocker, cli_browser
bdata budget            # confirms account + balance

If any of these fail, route to Path C (auth) before continuing.

Install agent skills (optional, recommended)

The CLI ships an installer that drops Bright Data skills directly into your coding agent's skill directory:

# Interactive picker — choose skills + target agent
bdata skill add

# Install a specific skill
bdata skill add scrape
bdata skill add data-feeds
bdata skill add competitive-intel

# See everything available
bdata skill list

These are the skills you'll hand off to from the paths below (scrape, search, data-feeds, scraper-builder, brightdata-cli, bright-data-mcp, …).

Choose your path

All paths share the same install + auth above. The difference is what you do next.

If your task spans paths, do them in order: auth → live tools to explore → app integration once the shape is known.

Path A — Live web tools (CLI)

Use this when the agent itself needs web data right now: discovering URLs, fetching clean content, pulling structured records from a known platform, or running a quick competitive scan.

After install + login, hand off to the narrower skills:

• brightdata-cli — overall command surface (scrape, search,

pipelines, status, zones, budget, config)

• search — discovery via bdata search (Google / Bing / Yandex

SERP, structured JSON)

• scrape — clean content from a known URL via bdata scrape

(markdown / HTML / JSON / screenshot)

• data-feeds — structured records from 40+ supported platforms via

bdata pipelines <type> (Amazon, LinkedIn, Instagram, TikTok, YouTube, Reddit, Crunchbase, Google Maps, …)

• competitive-intel — packaged competitor / pricing / review /

hiring / SEO analyses on top of the CLI

• seo-audit — sitemap-stratified live SEO audits

Default flow for live web work:

1. Search first when you need discovery

bdata search "query" --json

1. Pipelines next if the target is a supported platform — you get

structured JSON with no parsing bdata pipelines amazon_product "https://amazon.com/dp/..."

1. Scrape when you have a URL and no platform pipeline applies

bdata scrape "https://example.com" -f markdown

1. Browser API only when the page truly needs clicks, forms, or

login (see the brightdata-cli skill for bdata browser and the bright-data-best-practices browser-api reference)

When the task shifts from "fetch data now" to "wire this into an app," switch to Path B.

Path B — Integrate Bright Data into an app

Use this when you're building an application, agent, or workflow that calls Bright Data from code and needs BRIGHTDATA_API_KEY (and a zone) in .env or runtime config.

The required question on this path is:

What should Bright Data do in the product?

Use the answer to pick the API:

Pick a stack

• Python → use the official SDK

  pip install brightdata-sdk

Hand off to python-sdk-best-practices for client setup (async/sync), platform scrapers, SERP, datasets, Browser API, and error handling.

• Node / TypeScript / shell / other → call the REST API directly

(Path D below has the endpoints), or use the CLI as a library via npx @brightdata/cli.

• LLM tool layer (Claude, ChatGPT, etc.) → use the MCP server

(Path M).

Set credentials

BRIGHTDATA_API_KEY=...
BRIGHTDATA_UNLOCKER_ZONE=cli_unlocker   # created automatically by `bdata login`
BRIGHTDATA_SERP_ZONE=cli_unlocker       # or a dedicated SERP zone

If you don't have a key yet, do Path C first.

Smoke test before writing real code

Always run one real Bright Data request before scaling up integration work — catches auth, zone, and quota issues before they hide inside your app's error paths.

# Web Unlocker via REST
curl -sS https://api.brightdata.com/request \
  -H "Authorization: Bearer $BRIGHTDATA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://example.com",
    "zone": "'"$BRIGHTDATA_UNLOCKER_ZONE"'",
    "format": "raw",
    "data_format": "markdown"
  }' | head -40

If this prints clean markdown, you're wired up. If not, check the zone name and key.

Path M — MCP server (LLM tool layer)

Use this when the consumer is an LLM agent that should call Bright Data as tools (e.g., Claude Code, ChatGPT desktop, custom agent loops). The MCP server exposes 60+ tools — search, scrape, structured data per platform, browser automation — over a single URL.

Connect with:

https://mcp.brightdata.com/mcp?token=YOUR_BRIGHTDATA_API_TOKEN

Optional URL parameters:

Hand off to the bright-data-mcp skill for tool selection, tool-group auto-enabling, and workflow patterns. That skill explicitly replaces WebFetch / WebSearch with Bright Data MCP equivalents.

Path C — Get an API key (auth only)

Use this when the human still needs to sign up, sign in, or generate a key. Skip this path if bdata config already shows an authenticated account, or if BRIGHTDATA_API_KEY is already set in the environment.

Easiest: use the CLI's OAuth flow

bdata login            # browser-based OAuth
bdata login --device   # headless / SSH (device-code flow)

This handles signup-or-signin, key generation, zone creation, and local config in one step. Prefer this over manual flows.

Manual: dashboard

If the human prefers the web UI:

1. Go to https://brightdata.com/cp (sign up if needed)
2. Create a Web Unlocker zone ("Add" → "Unlocker zone")
3. Copy the API key from the dashboard
4. Save it where the rest of the app reads secrets:

echo "BRIGHTDATA_API_KEY=..." >> .env
echo "BRIGHTDATA_UNLOCKER_ZONE=<zone-name>" >> .env

Verify

bdata budget    # any successful response means the key works

If verification fails, the key is wrong, the zone is wrong, or the account has no active subscription — surface the error to the human rather than guessing.

Path D — Use Bright Data without installing anything

Use this when the environment can't run npm / curl | bash, or when you only need one or two requests and don't want the CLI / SDK. Works for both live agent work and app integration.

You still need an API key and a zone. Two ways to get them:

• Human pastes it in — if a key already exists, set

BRIGHTDATA_API_KEY=... and BRIGHTDATA_UNLOCKER_ZONE=... in the environment

• Browser flow — do Path C; the dashboard issues both

Base URL: https://api.brightdata.com Auth header: Authorization: Bearer $BRIGHTDATA_API_KEY

Core endpoints

# Web Unlocker — clean content from any URL
POST /request
{
  "url": "https://target.com",
  "zone": "<unlocker-zone>",
  "format": "raw",
  "data_format": "markdown"   // or "html", "screenshot", "parsed_light"
}

# SERP API — structured search results
# Use the same /request endpoint with a SERP zone and a search URL,
# adding `brd_json=1` to receive parsed JSON instead of raw HTML.
POST /request
{
  "url": "https://www.google.com/search?q=web+scraping&brd_json=1",
  "zone": "<serp-zone>",
  "format": "raw"
}

# Web Scraper API — structured data for 40+ platforms (async)
POST /datasets/v3/trigger?dataset_id=<id>
[ { "url": "https://amazon.com/dp/B09V3KXJPB" } ]

# then poll
GET  /datasets/v3/snapshot/<snapshot_id>?format=json

For the full parameter surface (special headers like x-unblock-expect, async response IDs, dataset progress states, Browser API CDP commands), read the bright-data-best-practices skill — its references are the source of truth for REST-level work.

Documentation

• Product docs: https://docs.brightdata.com
• LLM-friendly docs index: https://docs.brightdata.com/llms.txt
• Dashboard (zones, keys, billing): https://brightdata.com/cp

After onboarding — where to go next

Once the agent is set up, route the work to the narrowest skill that fits. Quick map:

When in doubt, prefer the more specific skill: data-feeds over scrape for supported platforms, scraper-builder over scrape for multi-page extraction, bright-data-mcp over brightdata-cli when the consumer is an LLM agent rather than a human at a terminal.