Bright Data Plugin for Claude Code

Unlock the web with AI-powered scraping, search, and structured data

Quick Start • Skills • Data Feeds • MCP • CLI • Competitive Intel • Scraper Builder • Best Practices • Python SDK • Setup • Examples

Overview

This plugin brings Bright Data's powerful web infrastructure directly into Claude Code, enabling AI agents to:

Scrape any webpage as clean markdown — bypassing bot detection, CAPTCHAs, and JavaScript rendering
Search Google with structured JSON results — titles, links, and descriptions ready for processing
Extract structured data from 40+ websites — Amazon, LinkedIn, Instagram, TikTok, YouTube, and more
Orchestrate 60+ MCP tools — search, scrape, extract structured data, and automate browsers via Bright Data's MCP server
Use the Bright Data CLI — scrape, search, extract data, manage zones, and check budget directly from the terminal with brightdata / bdata
Run competitive intelligence — real-time competitor analysis, pricing monitoring, review mining, hiring signal analysis, and market landscape mapping using live web data
Write correct Bright Data code — built-in best practices for Web Unlocker, SERP API, Web Scraper API, and Browser API
Build with the Python SDK — comprehensive guide for the brightdata-sdk package with patterns for async/sync clients, platform scrapers, SERP, datasets, and more

Built on Bright Data's Web Unlocker, SERP API, and Web Data APIs, this plugin handles the complexity of web access so your AI agents can focus on what matters.

Skills

Skill	Description
`search`	Search Google and get structured JSON results with titles, links, and descriptions
`scrape`	Scrape any webpage as clean markdown with automatic bot detection bypass
`data-feeds`	Extract structured data from 40+ websites with automatic polling
`bright-data-mcp`	Orchestrate 60+ Bright Data MCP tools for search, scraping, structured extraction, and browser automation
`scraper-builder`	Build production-ready scrapers for any website — guides through site analysis, API selection, selector extraction, pagination, and complete implementation. Triggers on "build a scraper for..."
`bright-data-best-practices`	Built-in reference for Web Unlocker, SERP API, Web Scraper API, and Browser API — Claude consults this automatically when writing Bright Data code
`python-sdk-best-practices`	Comprehensive guide for the `brightdata-sdk` Python package — async/sync clients, platform scrapers, SERP, datasets, Scraper Studio, Browser API, error handling, and common patterns
`brightdata-cli`	Guide for using the Bright Data CLI (`brightdata` / `bdata`) to scrape, search, extract structured data from 40+ platforms, manage proxy zones, and check account budget — all from the terminal
`competitive-intel`	Real-time competitive intelligence using live web data — competitor snapshots, pricing comparison, review mining, hiring signal analysis, content & SEO battles, and market landscape mapping. Replaces $15K+/yr enterprise CI tools at pennies per analysis
`design-mirror`	Replicates design system patterns, tokens, and components to build consistent, high-quality UIs
`brd-browser-debug`	Debug Bright Data Scraping Browser sessions — smart triage of failures, per-session bandwidth tracking, captcha reporting, and pattern detection using the Browser Sessions API

Quick Start

1. Get Your Credentials

Sign up at brightdata.com if you haven't already
Go to the Bright Data Dashboard
Create a Web Unlocker zone: Click "Add" → Select "Unlocker zone"
Copy your API Key from the dashboard

2. Set Environment Variables

export BRIGHTDATA_API_KEY="your-api-key"
export BRIGHTDATA_UNLOCKER_ZONE="your-zone-name"

3. Start Using

# Search Google
bash skills/search/scripts/search.sh "artificial intelligence trends"

# Scrape a webpage
bash skills/scrape/scripts/scrape.sh "https://example.com/article"

# Get LinkedIn profile data
bash skills/data-feeds/scripts/datasets.sh linkedin_person_profile "https://linkedin.com/in/satyanadella"

Bright Data MCP Skill

The bright-data-mcp skill teaches Claude how to optimally use Bright Data's MCP server — selecting the right tool, handling errors, and following best practices across 60+ tools.

MCP Server Connection

Connect the Bright Data MCP server using the remote URL:

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

Optional parameters:

Parameter	Description	Example
`pro=1`	Enable all 60+ Pro tools	`...&pro=1`
`groups=<name>`	Enable specific tool groups	`...&groups=social,ecommerce`
`tools=<names>`	Enable specific tools only	`...&tools=search_engine,scrape_as_markdown`

Available Tool Groups

Group	Tools	Platforms
Rapid (Free)	`search_engine`, `scrape_as_markdown`	Google/Bing/Yandex search, any webpage
ecommerce	11 tools	Amazon, Walmart, eBay, Best Buy, Etsy, Home Depot, Zara, Google Shopping
social	22 tools	LinkedIn, Instagram, Facebook, TikTok, YouTube, X, Reddit
business	4 tools	Crunchbase, ZoomInfo, Google Maps, Zillow
finance	1 tool	Yahoo Finance
research	2 tools	Reuters, GitHub
app_stores	2 tools	Google Play, Apple App Store
travel	1 tool	Booking.com
browser	13 tools	Full browser automation (navigate, click, type, screenshot)
advanced_scraping	5 tools	HTML scraping, AI extraction, batch operations

Claude Code Setup

Add to your MCP settings:

{
  "mcpServers": {
    "brightdata": {
      "url": "https://mcp.brightdata.com/mcp?token=YOUR_TOKEN&pro=1"
    }
  }
}

Why This Skill Matters

The bright-data-mcp skill ensures Bright Data MCP is always the default for all web data tasks — replacing built-in tools like WebFetch and WebSearch with superior alternatives that handle bot detection, CAPTCHAs, and JavaScript rendering automatically.

With this skill:

Default web tool — Claude always uses Bright Data MCP for any web data request, no exceptions
Replaces built-in tools — search_engine replaces WebSearch, scrape_as_markdown replaces WebFetch
Automatic tool selection — the most specific tool is chosen based on the task
Structured data preferred — web_data_* tools used over raw scraping when available
Error handling — built-in fallback strategies and URL validation guidance
Workflow orchestration — multi-step workflows for research, competitive analysis, social monitoring, and lead generation

Competitive Intel Skill

The competitive-intel skill turns Bright Data's scraping infrastructure into real-time competitive intelligence — replacing $15K–$50K/year enterprise CI tools (Crayon, Klue, AlphaSense) with an AI-native alternative that costs pennies per analysis.

How it works

The skill combines live web data (via bdata CLI) with strategic analysis frameworks to deliver actionable competitive insights — not stale training knowledge.

Say "analyze my competitor" or "compare pricing" and Claude will:

Gather live data using bdata search, bdata scrape, and bdata pipelines
Apply the appropriate analytical framework (SWOT, Porter's Five Forces, positioning matrix, etc.)
Deliver a structured report with source citations and strategic recommendations

Analysis modules

Module	What it does	Data sources
Competitor Snapshot	Quick profile: positioning, pricing, team, funding, strengths/weaknesses	`bdata scrape` (website), `bdata pipelines` (Crunchbase, LinkedIn)
Pricing Intelligence	Compare pricing across competitors with positioning analysis	`bdata scrape` (pricing pages), `bdata search` (third-party reviews)
Review Intelligence	Mine customer reviews for pain points, loved features, and gaps	`bdata scrape` (G2, Capterra), `bdata pipelines` (app stores, Google Maps)
Hiring Signal Analysis	Infer strategic direction from job postings	`bdata pipelines` (LinkedIn jobs), `bdata scrape` (careers pages)
Content & SEO Battle	Compare content strategy and search positioning	`bdata search` (SERP rankings), `bdata scrape` (blogs)
Market Landscape Map	Discover and categorize all players in a market	`bdata search` (discovery), `bdata scrape` (homepages), `bdata pipelines` (Crunchbase)

Example usage

> Analyze Notion as a competitor. I'm building a PM tool for small teams.

# Claude will:
# 1. Search Google for Notion
# 2. Scrape notion.com, /pricing, /about
# 3. Pull Crunchbase and LinkedIn data
# 4. Deliver a structured Competitor Snapshot with
#    pricing table, messaging analysis, strengths,
#    vulnerabilities, and strategic recommendations

> Compare pricing between Slack, Teams, and Discord

# Claude will:
# 1. Scrape all three pricing pages
# 2. Normalize into comparison matrix
# 3. Identify pricing models and positioning opportunities
# 4. Deliver a Pricing Intelligence Report

Reference files

skills/competitive-intel/SKILL.md — Main skill with 6 analysis modules and CLI command patterns
skills/competitive-intel/references/data-source-guide.md — Maps 30+ CI needs to specific bdata commands
skills/competitive-intel/references/output-templates.md — 8 report templates (Snapshot, Pricing, Reviews, Hiring, Content, Landscape, Battlecard, Executive Summary)
skills/competitive-intel/references/analysis-frameworks.md — SWOT, Porter's Five Forces, positioning matrix, Jobs-to-be-Done, Blue Ocean, Win/Loss
skills/competitive-intel/references/industry-signals.md — How to interpret pricing, hiring, content, review, funding, and social signals

Scraper Builder Skill

The scraper-builder skill guides you through building production-ready web scrapers for any website. Say "build a scraper for [site]" and Claude will walk you through the entire process.

How it works

The skill follows a 6-phase workflow:

Understand the target — What site, what data, what scope?
Check for pre-built scrapers — Searches 100+ supported domains via the Dataset List API before writing any custom code
Site reconnaissance — Fetches HTML via Web Unlocker, analyzes rendering (SSR vs CSR), discovers hidden APIs and JSON-LD data
Build the extractor — Picks the right approach: Web Unlocker + parsing, direct API endpoint, or Browser API with Playwright
Handle pagination — URL params, next-links, cursor tokens, infinite scroll, load-more buttons, sitemap crawling
Assemble complete scraper — Runnable script with config, fetcher, parser, paginator, output, and error handling

API selection logic

Scenario	API Used
Site has pre-built scraper (Amazon, LinkedIn, etc.)	Web Scraper API
Static HTML, no interaction needed	Web Unlocker
Site exposes JSON API internally	Web Unlocker → API endpoint
JS-rendered (React, Vue, Angular)	Browser API
Infinite scroll / click required	Browser API
Search engine results	SERP API

Example usage

> build a scraper for Amazon product pages, I have 50 ASINs

# Claude will:
# 1. Find Amazon's pre-built scraper
# 2. Use async trigger/poll/fetch for the batch
# 3. Output a complete Python script with structured JSON

> scrape all job listings from jobs.customsite.com with pagination

# Claude will:
# 1. Check for pre-built scraper (not found)
# 2. Fetch HTML to analyze structure
# 3. Pick Web Unlocker + BeautifulSoup
# 4. Handle pagination automatically
# 5. Output a complete working scraper

Reference files

skills/scraper-builder/SKILL.md — Main skill with decision tree and code patterns
skills/scraper-builder/references/supported-domains.md — Pre-built scraper lookup + dynamic Dataset List API
skills/scraper-builder/references/site-analysis-guide.md — HTML analysis playbook, selector strategy, hidden API discovery
skills/scraper-builder/references/pagination-patterns.md — 7 pagination strategies with complete code examples

Brightdata CLI Skill

The brightdata-cli skill teaches Claude how to use the Bright Data CLI (brightdata or bdata) — a terminal tool for scraping, searching, structured data extraction, zone management, and budget monitoring.

Quick start

# One-time login (auto-creates zones, saves API key)
brightdata login

# Scrape any URL as markdown
brightdata scrape https://example.com

# Search Google with structured results
brightdata search "web scraping best practices"

# Extract LinkedIn profile data
brightdata pipelines linkedin_person_profile "https://linkedin.com/in/username"

# Check account balance
brightdata budget

Key commands

Command	Purpose
`brightdata scrape <url>`	Scrape any URL as markdown, HTML, JSON, or screenshot
`brightdata search "<query>"`	Search Google/Bing/Yandex with structured results
`brightdata pipelines <type> [params]`	Extract structured data from 40+ platforms
`brightdata status <job-id>`	Check async job status
`brightdata zones`	List proxy zones
`brightdata budget`	View account balance and costs
`brightdata skill add`	Install AI agent skills
`brightdata config`	View/set configuration

Pipe-friendly

# Search → extract first URL → scrape it
brightdata search "top open source projects" --json \
  | jq -r '.organic[0].link' \
  | xargs brightdata scrape

# Amazon product data to CSV
brightdata pipelines amazon_product "https://amazon.com/dp/xxx" --format csv > product.csv

Reference files

skills/brightdata-cli/SKILL.md — Main skill with command overview and usage patterns
skills/brightdata-cli/references/commands.md — Full command reference with all flags and options
skills/brightdata-cli/references/pipelines.md — 40+ pipeline types with platform-specific parameters

Best Practices Skill

The bright-data-best-practices skill is a reference knowledge base that Claude consults automatically when writing or reviewing Bright Data code. It is not a slash command — it works silently in the background.

What it covers

API	Key topics
Web Unlocker	All request parameters, special headers (`x-unblock-expect`, `x-unblock-data-format`), async flow, billing model, anti-patterns
SERP API	All Google params (Search, Maps, Trends, Reviews, Lens, Hotels, Flights), Bing params, `brd_json=1` parsed output, async with `x-response-id`
Web Scraper API	Sync `/scrape` vs async `/trigger`, progress polling, status values, snapshot lifecycle, output formats
Browser API	Connection strings by framework, session rules, all custom CDP functions (`Captcha.solve`, `Proxy.setLocation`, `Emulation.setDevice`, etc.), bandwidth optimization

How it works

The skill has user-invocable: false — it never appears in the / command menu. Instead, Claude loads its reference material when you ask it to write Bright Data integrations, ensuring generated code uses correct endpoints, real parameter names, and proper patterns.

Reference files

Python SDK Best Practices Skill

The python-sdk-best-practices skill is a comprehensive guide for writing correct code with the brightdata-sdk Python package. Claude consults this automatically when writing, modifying, or reviewing Python code that uses the Bright Data SDK.

What it covers

Topic	Details
Client setup	Async (`BrightDataClient`) and sync (`SyncBrightDataClient`) clients, context managers, authentication
Platform scrapers	Amazon, LinkedIn, Instagram, Facebook, YouTube, ChatGPT, TikTok, Reddit — URL-based and keyword search
SERP API	Google, Bing, Yandex search with location, language, device, and async mode
Datasets API	175+ pre-collected datasets with filter, download, sample, and export
Scraper Studio	Custom scraper execution with trigger/poll/fetch lifecycle
Browser API	CDP WebSocket URLs for Playwright/Puppeteer automation
Error handling	Full exception hierarchy with `APIError.status_code`, `APIError.response_text`
Batch operations	Concurrent scraping with `asyncio.gather()`
Common mistakes	Forgetting context managers, sync in async, missing `await`, hardcoded tokens

Reference files

skills/python-sdk-best-practices/SKILL.md — Core patterns and best practices
skills/python-sdk-best-practices/references/api-reference.md — Full API surface, service hierarchy, payload models, constants

Setup

Prerequisites

Dependency	Version	Description
`curl`	≥ 7.0	HTTP client for API requests
`jq`	≥ 1.5	JSON processor for parsing responses

Install on Ubuntu/Debian:

sudo apt-get install curl jq

Install on macOS:

brew install curl jq

Environment Variables

Variable	Required	Description
`BRIGHTDATA_API_KEY`	Yes	Your Bright Data API key from the dashboard
`BRIGHTDATA_UNLOCKER_ZONE`	Yes*	Name of your Web Unlocker zone (*required for search/scrape)
`BRIGHTDATA_POLLING_TIMEOUT`	No	Max seconds to wait for data-feeds (default: 600)

Usage

Search Skill

Search Google and receive structured JSON results.

bash skills/search/scripts/search.sh "query" [page]

Parameters:

Parameter	Required	Default	Description
`query`	Yes	-	Search query string
`page`	No	`0`	Page number (0-indexed) for pagination

Output Format:

{
  "organic": [
    {
      "link": "https://example.com/result",
      "title": "Result Title",
      "description": "Brief description of the page..."
    }
  ]
}

Scrape Skill

Scrape any webpage and get clean markdown content.

bash skills/scrape/scripts/scrape.sh "url"

Features:

Automatic bot detection bypass
CAPTCHA solving
JavaScript rendering
Clean markdown output

Data Feeds Skill

Extract structured data from 40+ supported websites.

bash skills/data-feeds/scripts/datasets.sh <dataset_type> <url> [params...]

Run without arguments to see all available datasets:

bash skills/data-feeds/scripts/datasets.sh

Data Feeds

E-Commerce

Dataset	Command	Description
Amazon Product	`datasets.sh amazon_product <url>`	Product details, pricing, ratings
Amazon Reviews	`datasets.sh amazon_product_reviews <url>`	Customer reviews
Amazon Search	`datasets.sh amazon_product_search <keyword> <domain>`	Search results
Walmart Product	`datasets.sh walmart_product <url>`	Product details
eBay Product	`datasets.sh ebay_product <url>`	Listing details
Best Buy	`datasets.sh bestbuy_products <url>`	Product info
Etsy	`datasets.sh etsy_products <url>`	Listing data
Home Depot	`datasets.sh homedepot_products <url>`	Product data
Zara	`datasets.sh zara_products <url>`	Product details

Professional Networks

Dataset	Command	Description
LinkedIn Person	`datasets.sh linkedin_person_profile <url>`	Profile, experience, skills
LinkedIn Company	`datasets.sh linkedin_company_profile <url>`	Company page data
LinkedIn Jobs	`datasets.sh linkedin_job_listings <url>`	Job posting details
LinkedIn Posts	`datasets.sh linkedin_posts <url>`	Post content
Crunchbase	`datasets.sh crunchbase_company <url>`	Funding, employees
ZoomInfo	`datasets.sh zoominfo_company_profile <url>`	Company profile

Dataset	Command	Description
Instagram Profiles	`datasets.sh instagram_profiles <url>`	Bio, followers
Instagram Posts	`datasets.sh instagram_posts <url>`	Post details
Instagram Reels	`datasets.sh instagram_reels <url>`	Reel metrics
TikTok Profiles	`datasets.sh tiktok_profiles <url>`	Creator data
TikTok Posts	`datasets.sh tiktok_posts <url>`	Video details
TikTok Shop	`datasets.sh tiktok_shop <url>`	Product data
Facebook Posts	`datasets.sh facebook_posts <url>`	Post content
Facebook Marketplace	`datasets.sh facebook_marketplace_listings <url>`	Listings
X (Twitter)	`datasets.sh x_posts <url>`	Tweet data
YouTube Profiles	`datasets.sh youtube_profiles <url>`	Channel data
YouTube Videos	`datasets.sh youtube_videos <url>`	Video details
YouTube Comments	`datasets.sh youtube_comments <url> [num]`	Comments
Reddit Posts	`datasets.sh reddit_posts <url>`	Post data

Other

Dataset	Command	Description
Google Maps Reviews	`datasets.sh google_maps_reviews <url> [days]`	Business reviews
Google Shopping	`datasets.sh google_shopping <url>`	Product comparison
Google Play Store	`datasets.sh google_play_store <url>`	App details
Apple App Store	`datasets.sh apple_app_store <url>`	iOS app data
Yahoo Finance	`datasets.sh yahoo_finance_business <url>`	Stock data
Zillow	`datasets.sh zillow_properties_listing <url>`	Property listings
Booking.com	`datasets.sh booking_hotel_listings <url>`	Hotel data
Reuters News	`datasets.sh reuter_news <url>`	Article content
GitHub	`datasets.sh github_repository_file <url>`	Repository file

Examples

Research Task

# Search for recent news
bash skills/search/scripts/search.sh "climate change 2024"

# Get full article content
bash skills/scrape/scripts/scrape.sh "https://example.com/climate-article"

Competitive Analysis

# With the competitive-intel skill, just ask Claude:
# "Analyze Notion as a competitor" or "Compare pricing between Slack and Teams"
# Claude will automatically run the right bdata commands:

# Search for competitor info
bdata search "Notion project management" --json

# Scrape competitor pricing page
bdata scrape https://www.notion.com/pricing

# Get company data from Crunchbase
bdata pipelines crunchbase_company "https://www.crunchbase.com/organization/notion-so"

# Get LinkedIn company profile
bdata pipelines linkedin_company_profile "https://www.linkedin.com/company/notionhq"

# Get Instagram profile
bash skills/data-feeds/scripts/datasets.sh instagram_profiles "https://instagram.com/natgeo"

# Get YouTube video stats
bash skills/data-feeds/scripts/datasets.sh youtube_videos "https://youtube.com/watch?v=dQw4w9WgXcQ"

Lead Generation

# Get LinkedIn profile
bash skills/data-feeds/scripts/datasets.sh linkedin_person_profile "https://linkedin.com/in/satyanadella"

# Get company funding data
bash skills/data-feeds/scripts/datasets.sh crunchbase_company "https://crunchbase.com/organization/openai"

Project Structure

brightdata-plugin/
├── .claude-plugin/
│   ├── plugin.json              # Plugin configuration
│   └── marketplace.json         # Marketplace metadata
├── skills/
│   ├── search/
│   │   ├── SKILL.md             # Search skill
│   │   └── scripts/
│   │       └── search.sh        # Google search implementation
│   ├── scrape/
│   │   ├── SKILL.md             # Scrape skill
│   │   └── scripts/
│   │       └── scrape.sh        # Web scraper implementation
│   ├── data-feeds/
│   │   ├── SKILL.md             # Data feeds skill
│   │   └── scripts/
│   │       ├── datasets.sh      # Dataset wrapper (40+ sources)
│   │       └── fetch.sh         # Core polling logic
│   ├── bright-data-mcp/
│   │   ├── SKILL.md             # MCP workflow guide
│   │   └── references/
│   │       ├── mcp-tools.md     # Complete MCP tool reference (60+ tools)
│   │       └── mcp-setup.md     # MCP server setup guide
│   ├── bright-data-best-practices/
│   │   ├── SKILL.md             # API best practices (user-invocable: false)
│   │   └── references/
│   │       ├── web-unlocker.md  # Web Unlocker API deep reference
│   │       ├── serp-api.md      # SERP API deep reference
│   │       ├── web-scraper-api.md  # Web Scraper API deep reference
│   │       └── browser-api.md   # Browser API deep reference
│   ├── python-sdk-best-practices/
│   │   ├── SKILL.md             # Python SDK patterns and best practices
│   │   └── references/
│   │       └── api-reference.md # Full API surface, payloads, constants
│   ├── scraper-builder/
│   │   ├── SKILL.md             # Scraper builder workflow and decision tree
│   │   └── references/
│   │       ├── supported-domains.md   # Pre-built scraper lookup + API
│   │       ├── site-analysis-guide.md # HTML analysis playbook
│   │       └── pagination-patterns.md # 7 pagination strategies
│   ├── brightdata-cli/
│   │   ├── SKILL.md             # CLI usage guide and command patterns
│   │   └── references/
│   │       ├── commands.md      # Full command reference with all flags
│   │       └── pipelines.md     # 40+ pipeline types and parameters
│   ├── competitive-intel/
│   │   ├── SKILL.md             # Competitive intelligence (6 analysis modules)
│   │   └── references/
│   │       ├── data-source-guide.md    # CI needs → bdata command mapping
│   │       ├── output-templates.md     # 8 report templates
│   │       ├── analysis-frameworks.md  # SWOT, Porter's, positioning, JTBD, Blue Ocean
│   │       └── industry-signals.md     # Signal interpretation guide
│   └── design-mirror/
│       └── SKILL.md             # Design system mirroring skill
├── sdk-python/                  # Bright Data Python SDK source
├── README.md
└── LICENSE

API Reference

Search & Scrape (Web Unlocker API)

POST https://api.brightdata.com/request
Authorization: Bearer <BRIGHTDATA_API_KEY>
Content-Type: application/json

{
  "url": "<target_url>",
  "zone": "<BRIGHTDATA_UNLOCKER_ZONE>",
  "format": "raw",
  "data_format": "markdown" | "parsed_light"
}

Data Feeds (Web Data API)

POST https://api.brightdata.com/datasets/v3/trigger?dataset_id=<id>
Authorization: Bearer <BRIGHTDATA_API_KEY>
Content-Type: application/json

[{"url": "<target_url>"}]

Then poll for results:

GET https://api.brightdata.com/datasets/v3/snapshot/<snapshot_id>?format=json

Troubleshooting

"BRIGHTDATA_API_KEY is not set"

export BRIGHTDATA_API_KEY="your-api-key"

"BRIGHTDATA_UNLOCKER_ZONE is not set"

Create a Web Unlocker zone in your dashboard:

export BRIGHTDATA_UNLOCKER_ZONE="your-zone-name"

Data feeds timing out

Increase the polling timeout:

export BRIGHTDATA_POLLING_TIMEOUT=900

Empty or malformed results

Verify your API key is valid
Check that your zone is active
Ensure jq is installed

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Fork the repository
Create your feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Bright Data Plugin for Claude Code

Overview

Skills

Quick Start

1. Get Your Credentials

2. Set Environment Variables

3. Start Using

Bright Data MCP Skill

MCP Server Connection

Available Tool Groups

Claude Code Setup

Why This Skill Matters

Competitive Intel Skill

How it works

Analysis modules

Example usage

Reference files

Scraper Builder Skill

How it works

API selection logic

Example usage

Reference files

Brightdata CLI Skill

Quick start

Key commands

Pipe-friendly

Reference files

Best Practices Skill

What it covers

How it works

Reference files

Python SDK Best Practices Skill

What it covers

Reference files

Setup

Prerequisites

Environment Variables

Usage

Search Skill

Scrape Skill

Data Feeds Skill

Data Feeds

E-Commerce

Professional Networks

Social Media

Other

Examples

Research Task

Competitive Analysis

Social Media Monitoring

Lead Generation

Project Structure

API Reference

Search & Scrape (Web Unlocker API)

Data Feeds (Web Data API)

Troubleshooting

"BRIGHTDATA_API_KEY is not set"

"BRIGHTDATA_UNLOCKER_ZONE is not set"

Data feeds timing out

Empty or malformed results

Contributing

License

Links