agent-onboarding

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Translated

Onboard an agent to Bright Data. Use when a coding agent first encounters Bright Data — for live web work (search, scrape, structured data), for wiring Bright Data into product code, for installing the agent skill bundle, or for getting an API key. One install command sets up the CLI, agent skills, and authentication. Routes the reader to the right path: live tools, app integration, MCP, auth-only, or direct REST without any install.

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NPX Install

npx skill4agent add brightdata/skills agent-onboarding

Tags

Translated version includes tags in frontmatter

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:
bash
# 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:
bash
bdata login
This single command:
  1. Opens the browser for OAuth (or use
    bdata login --device
    on headless / SSH machines)
  2. Saves the API key locally — you never need to paste a token again
  3. Auto-creates the required proxy zones (
    cli_unlocker
    ,
    cli_browser
    )
  4. Sets sensible default configuration
For non-interactive setups you can pass the key directly:
bash
bdata login --api-key <key>
# or
export BRIGHTDATA_API_KEY=<key>
Verify the install before doing real work:
bash
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:
bash
# 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.
SituationPath
Need web data during this sessionPath A — live CLI tools
Need to add Bright Data to app codePath B — SDK / REST integration
Want a drop-in tool layer for an LLM agentPath M — MCP server
Need an API key firstPath C — auth only
Don't want to install anythingPath D — REST API directly
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
  2. Pipelines next if the target is a supported platform — you get structured JSON with no parsing
    bdata pipelines amazon_product "https://amazon.com/dp/..."
  3. Scrape when you have a URL and no platform pipeline applies
    bdata scrape "https://example.com" -f markdown
  4. 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:
Job in productAPISkill
Fetch a single page as markdown / HTML / JSONWeb Unlocker
bright-data-best-practices
web-unlocker.md
Search engine results in structured JSONSERP API
bright-data-best-practices
serp-api.md
Structured records from supported platformsWeb Scraper API
bright-data-best-practices
web-scraper-api.md
JS-heavy / interactive pages with Playwright/PuppeteerBrowser API
bright-data-best-practices
browser-api.md
Build a custom scraper for an arbitrary siteAll four, picked by site shape
scraper-builder

Pick a stack

  • Python → use the official SDK
    bash
    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

dotenv
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.
bash
# 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:
ParameterEffect
pro=1
Enable all 60+ Pro tools
groups=<name>
Enable a tool group (
social
,
ecommerce
,
business
,
finance
,
research
,
app_stores
,
travel
,
browser
,
advanced_scraping
)
tools=<names>
Enable a specific tool list, comma-separated
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

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

Verify

bash
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

http
# 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"
}
http
# 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"
}
http
# 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


After onboarding — where to go next

Once the agent is set up, route the work to the narrowest skill that fits. Quick map:
User says…Skill
"scrape this URL" / "get this page"
scrape
"search Google for…" / "find URLs about…"
search
"get Amazon / LinkedIn / Instagram / TikTok / YouTube / Reddit data"
data-feeds
"build a scraper for <site>"
scraper-builder
"analyze my competitor" / "compare pricing"
competitive-intel
"audit SEO" / "rank check" / "schema check"
seo-audit
"write Bright Data code in Python"
python-sdk-best-practices
"plug Bright Data into my LLM agent"
bright-data-mcp
"use the CLI" / "run from terminal"
brightdata-cli
"debug a Browser API session"
brd-browser-debug
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.