{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-scrapingbee--n8n-no-code-web-scraper","slug":"scrapingbee--n8n-no-code-web-scraper","name":"n8n-no-code-web-scraper","type":"workflow","url":"https://www.scrapingbee.com/features/ai-web-scraping-api/","page_url":"https://unfragile.ai/scrapingbee--n8n-no-code-web-scraper","categories":["automation","app-builders"],"tags":["ai-automation","ai-automation-python","ai-data","ai-data-extraction","ai-powered-scraping","ai-web-scraper","chat-bot-api","n8n","n8n-workflow","no-code-scraping","proxies-scraper","proxy-scraper","scraper-api","scrapingbee","serp-scraper","web-scraping","web-scraping-api","web-scraping-project","web-scraping-python"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-scrapingbee--n8n-no-code-web-scraper__cap_0","uri":"capability://automation.workflow.visual.web.scraping.with.browser.rendering","name":"visual-web-scraping-with-browser-rendering","description":"Executes full browser rendering of target websites through ScrapingBee's cloud infrastructure, enabling extraction of dynamically-loaded content (JavaScript-rendered DOM) that would be invisible to simple HTTP requests. The workflow orchestrates headless browser automation via n8n's HTTP nodes calling ScrapingBee's API endpoints, handling cookie injection, JavaScript execution, and screenshot capture for visual verification of scraped content.","intents":["I need to scrape data from JavaScript-heavy single-page applications without building custom Puppeteer scripts","I want to extract content that only appears after page interactions or AJAX calls complete","I need to verify scraped data visually by capturing screenshots of rendered pages"],"best_for":["non-technical business analysts building data pipelines","teams migrating from manual web scraping to automated workflows","data engineers prototyping scraping solutions before production implementation"],"limitations":["Browser rendering adds 2-5 second latency per request vs static HTML parsing","ScrapingBee API rate limits apply (typically 5,000-50,000 requests/month depending on plan)","No built-in JavaScript execution customization — limited to standard browser environment","Screenshot capture increases response payload size and API quota consumption"],"requires":["n8n instance (self-hosted or cloud)","ScrapingBee API key with active subscription","HTTP request node support in n8n (included in core)","Network connectivity to ScrapingBee cloud infrastructure"],"input_types":["URL strings","JSON configuration objects (headers, cookies, parameters)"],"output_types":["HTML markup (rendered DOM)","JSON structured data","PNG/JPEG screenshots","Metadata (status codes, response times)"],"categories":["automation-workflow","web-scraping","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-scrapingbee--n8n-no-code-web-scraper__cap_1","uri":"capability://data.processing.analysis.ai.powered.content.extraction.with.structured.output","name":"ai-powered-content-extraction-with-structured-output","description":"Leverages LLM-based parsing to intelligently extract and structure unstructured HTML content into predefined JSON schemas without regex or CSS selectors. The workflow chains ScrapingBee's raw HTML output through an AI model (via n8n's AI nodes or external LLM APIs) with a schema prompt, enabling semantic understanding of page content and automatic field mapping even when HTML structure varies across pages.","intents":["I need to extract product details (price, description, ratings) from multiple e-commerce sites with different HTML structures","I want to parse semi-structured content like job listings or real estate listings into consistent JSON records","I need to handle pages where CSS selectors break due to dynamic class names or layout changes"],"best_for":["product teams building price comparison or market intelligence tools","data scientists preparing training datasets from web sources","business users without HTML/CSS knowledge who need flexible extraction"],"limitations":["LLM parsing adds 1-3 second latency per request and increases API costs (LLM tokens + ScrapingBee)","Hallucination risk if pages contain ambiguous or missing data — requires validation nodes","Schema definition must be precise; vague field descriptions lead to inconsistent extraction","No built-in error recovery if LLM fails to parse — requires manual workflow branching"],"requires":["n8n instance with AI node support (OpenAI, Anthropic, or local LLM integration)","LLM API key (OpenAI, Anthropic, Hugging Face, or self-hosted model)","ScrapingBee API key for HTML retrieval","JSON schema definition for target data structure"],"input_types":["HTML markup (from ScrapingBee or other sources)","JSON schema definition","Extraction prompt template"],"output_types":["JSON objects matching defined schema","Validation metadata (confidence scores, parsing errors)","Structured CSV/database records"],"categories":["data-processing-analysis","automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-scrapingbee--n8n-no-code-web-scraper__cap_10","uri":"capability://automation.workflow.batch.scraping.with.url.list.processing","name":"batch-scraping-with-url-list-processing","description":"Processes large lists of URLs (hundreds or thousands) through ScrapingBee in batches, using n8n's loop nodes to iterate over URL arrays while respecting rate limits and managing concurrent requests. The workflow handles batching strategies (sequential, parallel with concurrency limits), tracks progress, and aggregates results into a single output dataset for bulk analysis or storage.","intents":["I need to scrape 500 product pages from an e-commerce site and store all results in a database","I want to collect data from a list of competitor websites in parallel without overwhelming the API","I need to process a CSV file of URLs and generate a consolidated report"],"best_for":["data teams running bulk data collection jobs","market research firms gathering competitive intelligence at scale","teams migrating data from one system to another"],"limitations":["Sequential processing is slow for large lists (1000 URLs × 5 seconds = 83 minutes)","Parallel processing with high concurrency may hit ScrapingBee rate limits or trigger anti-bot detection","n8n memory usage grows with result set size — very large batches (100k+ URLs) may cause out-of-memory errors","No built-in progress persistence — if workflow fails mid-batch, all progress is lost (unless checkpointing is added)"],"requires":["n8n instance with loop/iterate node support","ScrapingBee API key with sufficient quota for batch size","URL list in CSV, JSON, or database query format","Concurrency limit configuration to avoid rate limiting"],"input_types":["CSV file with URL column","JSON array of URLs","Database query returning URL list"],"output_types":["Consolidated JSON array with all scraped results","CSV export of results","Database inserts for each URL","Progress metrics (URLs processed, success rate, average latency)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-scrapingbee--n8n-no-code-web-scraper__cap_2","uri":"capability://automation.workflow.proxy.rotation.and.anti.detection.management","name":"proxy-rotation-and-anti-detection-management","description":"Automatically rotates residential and datacenter proxies through ScrapingBee's managed proxy pool, injecting headers, user agents, and request timing to evade bot detection and IP blocking. The n8n workflow abstracts proxy configuration through ScrapingBee API parameters (proxy_type, country, residential flag) rather than managing proxy lists manually, handling failed requests with automatic retry logic and proxy switching.","intents":["I need to scrape high-volume data from sites that block scrapers or enforce rate limits","I want to distribute requests across geographic regions to appear as natural user traffic","I need to handle IP bans gracefully by automatically switching to fresh proxies on failure"],"best_for":["competitive intelligence teams monitoring competitor pricing/inventory","market research firms collecting data at scale","teams scraping sites with aggressive anti-bot measures (Cloudflare, WAF)"],"limitations":["Residential proxies add 3-8 second latency per request due to routing through real devices","ScrapingBee's proxy pool is shared — no guarantee of consistent IP addresses across requests","Some sites explicitly prohibit scraping in ToS — proxy rotation does not provide legal cover","Datacenter proxies are cheaper but more easily detected by modern bot detection (reCAPTCHA, Cloudflare)"],"requires":["ScrapingBee API key with residential proxy plan (higher tier than basic)","n8n workflow with retry logic and error handling nodes","Understanding of target site's anti-bot mechanisms (IP blocking vs JavaScript challenges)"],"input_types":["URL strings","Proxy configuration parameters (type: residential/datacenter, country code, sticky_proxies flag)"],"output_types":["HTML content from rotated proxy","Response metadata (proxy IP used, country, latency)","Retry attempt logs"],"categories":["automation-workflow","tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-scrapingbee--n8n-no-code-web-scraper__cap_3","uri":"capability://automation.workflow.scheduled.web.scraping.with.workflow.automation","name":"scheduled-web-scraping-with-workflow-automation","description":"Orchestrates recurring scraping jobs using n8n's cron-based scheduling engine, triggering ScrapingBee requests at fixed intervals (hourly, daily, weekly) and piping results into downstream storage or notification systems. The workflow manages job state, deduplication, and error notifications through n8n's conditional branching and webhook integrations, enabling fully automated data collection pipelines without manual intervention.","intents":["I need to monitor website changes (price drops, new listings, inventory updates) on a daily schedule","I want to collect historical data over time to build trend analysis datasets","I need to alert my team when scraped data meets certain conditions (e.g., price below threshold)"],"best_for":["e-commerce teams tracking competitor pricing","real estate platforms monitoring new listings","financial analysts collecting market data feeds","content teams monitoring news sources for mentions"],"limitations":["n8n scheduler has minute-level granularity but not sub-second precision — unsuitable for high-frequency trading","Workflow execution history grows unbounded — requires periodic cleanup or archival","No built-in deduplication — requires custom logic to detect and skip unchanged data","Self-hosted n8n requires persistent infrastructure; cloud n8n has execution time limits per workflow"],"requires":["n8n instance (self-hosted or cloud) with scheduler node enabled","ScrapingBee API key with sufficient monthly quota for scheduled frequency","Downstream storage (database, data warehouse, file storage) or notification service","Cron expression knowledge or n8n's visual scheduler UI"],"input_types":["Cron schedule expression (e.g., '0 9 * * *' for daily at 9 AM)","Target URL list","Extraction schema or CSS selectors"],"output_types":["Timestamped data records","Change detection logs","Notification payloads (email, Slack, webhook)","Database inserts or file appends"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-scrapingbee--n8n-no-code-web-scraper__cap_4","uri":"capability://automation.workflow.multi.page.crawling.with.link.traversal","name":"multi-page-crawling-with-link-traversal","description":"Implements recursive or iterative page crawling by extracting links from initial pages and feeding them back into ScrapingBee requests through n8n's loop nodes. The workflow maintains a crawl frontier (queue of URLs to visit), deduplicates visited URLs, and applies depth limits or URL pattern filters to prevent infinite crawls, enabling systematic exploration of site structure without custom crawler code.","intents":["I need to scrape all product pages from a category listing by following pagination links","I want to crawl a site's entire structure to build a sitemap or inventory","I need to extract data from linked resources (e.g., product details from category pages)"],"best_for":["e-commerce data teams building product catalogs","SEO tools crawling sites for technical audits","research teams mapping competitor site structures","content aggregators collecting articles across multiple pages"],"limitations":["Exponential URL explosion if crawl depth or breadth is not constrained — can quickly exhaust API quota","No built-in duplicate detection across workflow runs — requires external state store (database) for deduplication","Crawl speed is limited by ScrapingBee API rate limits and rendering latency — large sites may take hours","Memory constraints in n8n if URL queue grows very large (100k+ URLs) — may require pagination or batching"],"requires":["n8n instance with loop/iterate node support","ScrapingBee API key with sufficient quota for multi-page crawling","URL pattern matching logic (regex or simple string matching)","Optional: external database for visited URL tracking across workflow executions"],"input_types":["Seed URL (starting point)","Link selector (CSS selector or XPath to extract links)","Crawl constraints (max depth, max pages, URL pattern filter)"],"output_types":["Flattened list of all crawled pages with extracted data","Crawl tree/graph structure (parent-child relationships)","Sitemap format (XML or JSON)","Crawl statistics (pages visited, errors, duration)"],"categories":["automation-workflow","search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-scrapingbee--n8n-no-code-web-scraper__cap_5","uri":"capability://data.processing.analysis.data.validation.and.quality.assurance.in.pipeline","name":"data-validation-and-quality-assurance-in-pipeline","description":"Applies schema validation, type checking, and business logic assertions to scraped data within the n8n workflow before storage or downstream processing. The workflow uses n8n's conditional nodes and JavaScript expressions to validate field presence, data types, value ranges, and cross-field consistency, with automatic error routing to dead-letter queues or manual review workflows for invalid records.","intents":["I need to ensure scraped prices are numeric and within expected ranges before storing in database","I want to flag incomplete records (missing required fields) for manual review","I need to validate that extracted dates are in correct format and not in the future"],"best_for":["data quality teams ensuring scraping accuracy","teams feeding scraped data into analytics or ML pipelines","business users who need confidence in data before using it for decisions"],"limitations":["Validation logic must be hardcoded in n8n expressions — no declarative schema validation framework","Complex validations (cross-field dependencies, business rules) require custom JavaScript code","No built-in data profiling or anomaly detection — requires manual rule definition","Validation failures are logged but not automatically corrected — requires separate data cleaning step"],"requires":["n8n instance with conditional node and JavaScript expression support","Clear definition of data quality rules and acceptable value ranges","Optional: external database or queue for storing invalid records"],"input_types":["JSON records from scraping or AI extraction","Validation rule definitions (field requirements, type constraints, value ranges)"],"output_types":["Valid records (passed validation)","Invalid records with error messages","Validation metrics (pass rate, common failure types)"],"categories":["data-processing-analysis","automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-scrapingbee--n8n-no-code-web-scraper__cap_6","uri":"capability://automation.workflow.webhook.triggered.on.demand.scraping","name":"webhook-triggered-on-demand-scraping","description":"Exposes n8n workflows as HTTP webhooks, allowing external systems or user requests to trigger scraping jobs on-demand with custom parameters (URL, extraction schema, options). The webhook receives JSON payloads, validates inputs, invokes ScrapingBee, and returns results synchronously or asynchronously via callback URLs, enabling integration with chatbots, APIs, or frontend applications.","intents":["I want to expose scraping as an API endpoint that my frontend can call when users request data","I need to trigger scraping from a chatbot when users ask for product information","I want to integrate scraping into a larger API workflow without building custom backend code"],"best_for":["teams building chatbot integrations (Slack, Discord, Teams)","API developers adding scraping capabilities to existing services","product teams enabling user-triggered data collection in applications"],"limitations":["Webhook response time is limited by ScrapingBee latency (2-10 seconds) — unsuitable for sub-second requirements","n8n webhook URLs are public — requires authentication (API key, OAuth) to prevent abuse","Synchronous responses are limited by HTTP timeout (typically 30-60 seconds) — long scraping jobs must use async callbacks","No built-in rate limiting — requires external API gateway or n8n middleware for quota enforcement"],"requires":["n8n instance with webhook node enabled and publicly accessible URL","Authentication mechanism (API key, OAuth token, or IP whitelist)","Client application capable of making HTTP POST requests","Optional: callback URL for async result delivery"],"input_types":["JSON webhook payload with URL, extraction schema, proxy options","Query parameters for simple configurations"],"output_types":["JSON response with scraped data (synchronous)","HTTP 202 Accepted with job ID (asynchronous)","Callback POST to client-provided URL with results"],"categories":["automation-workflow","tool-use-integration","api-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-scrapingbee--n8n-no-code-web-scraper__cap_7","uri":"capability://automation.workflow.data.storage.and.database.integration","name":"data-storage-and-database-integration","description":"Routes scraped and validated data into multiple storage backends (PostgreSQL, MongoDB, Google Sheets, Airtable, S3, data warehouses) through n8n's native database and cloud storage connectors. The workflow handles batch inserts, upserts (update-or-insert), and incremental syncs, managing schema mapping between scraped JSON and database tables without custom ETL code.","intents":["I need to store scraped product data in a PostgreSQL database for analytics queries","I want to sync scraped data to Google Sheets for non-technical team members to view","I need to archive historical scraping results in S3 for compliance and trend analysis"],"best_for":["data engineers building data pipelines","teams needing multi-destination data distribution","organizations with existing data warehouse infrastructure"],"limitations":["n8n database connectors have limited transaction support — large batch inserts may fail partially without rollback","Schema evolution (adding/removing columns) requires manual workflow updates","No built-in data deduplication across multiple storage targets — requires custom logic","Cloud storage connectors (Google Sheets, Airtable) have API rate limits that may throttle large syncs"],"requires":["n8n instance with database connector nodes (PostgreSQL, MongoDB, MySQL, etc.)","Database credentials and connection strings","Target database/table schema matching scraped data structure","Optional: cloud storage credentials (AWS, Google Cloud, Azure)"],"input_types":["JSON records from scraping pipeline","Database connection configuration","Mapping rules (JSON field → database column)"],"output_types":["Database insert/update confirmations","Row counts and affected records","Error logs for failed inserts"],"categories":["automation-workflow","data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-scrapingbee--n8n-no-code-web-scraper__cap_8","uri":"capability://automation.workflow.error.handling.and.retry.logic","name":"error-handling-and-retry-logic","description":"Implements exponential backoff retry strategies, circuit breaker patterns, and error routing within n8n workflows to handle transient failures (network timeouts, rate limits, temporary service outages). The workflow catches ScrapingBee API errors, categorizes them (retryable vs permanent), and routes failures to dead-letter queues, notification channels, or manual review workflows based on error type.","intents":["I need my scraping workflow to automatically retry failed requests instead of stopping","I want to be notified when scraping fails persistently so I can investigate","I need to distinguish between temporary failures (retry) and permanent errors (skip)"],"best_for":["teams running production scraping pipelines requiring high reliability","operations teams managing 24/7 data collection","systems requiring SLA compliance (e.g., 99.5% uptime)"],"limitations":["Exponential backoff increases total execution time — may exceed workflow timeout limits","No built-in circuit breaker — requires custom logic to detect cascading failures","Error categorization must be manually defined — ScrapingBee error codes need mapping to retry decisions","Retry state is not persisted across n8n restarts — in-flight retries may be lost"],"requires":["n8n instance with error handling and conditional node support","Understanding of ScrapingBee error codes and HTTP status codes","Notification service (email, Slack, PagerDuty) for alerting","Optional: external queue or database for dead-letter storage"],"input_types":["Error responses from ScrapingBee API","Retry configuration (max attempts, backoff multiplier, timeout)"],"output_types":["Successful retry results","Dead-letter records (permanently failed)","Error notifications and logs"],"categories":["automation-workflow","safety-moderation","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-scrapingbee--n8n-no-code-web-scraper__cap_9","uri":"capability://automation.workflow.notification.and.alerting.on.data.changes","name":"notification-and-alerting-on-data-changes","description":"Monitors scraped data for significant changes (price drops, new listings, status updates) and triggers notifications via email, Slack, Discord, or webhooks when conditions are met. The workflow compares current scraping results against previous snapshots (stored in database or cache), calculates deltas, and routes alerts based on change magnitude or business rules.","intents":["I want to be alerted when a competitor's price drops below my threshold","I need to notify my team when new job listings appear on a career site","I want to track inventory changes and alert when stock becomes available"],"best_for":["competitive intelligence teams monitoring market changes","e-commerce teams tracking pricing and inventory","recruitment teams monitoring job boards","business users who need real-time alerts without technical setup"],"limitations":["Change detection requires comparing against previous state — first run has no baseline","Alert fatigue if thresholds are too sensitive — requires tuning and testing","Notification delivery is not guaranteed (email spam filters, Slack rate limits) — no built-in retry","No built-in deduplication — same alert may be sent multiple times if workflow runs frequently"],"requires":["n8n instance with conditional nodes and notification integrations","Previous data snapshot (database table, cache, or file)","Notification service credentials (Slack webhook, email SMTP, Discord bot token)","Change detection logic (threshold values, comparison operators)"],"input_types":["Current scraped data","Previous data snapshot","Alert threshold configuration (e.g., price_drop_percent: 10)"],"output_types":["Alert messages (Slack, email, Discord)","Change logs (what changed, old value, new value)","Notification delivery status"],"categories":["automation-workflow","planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":35,"verified":false,"data_access_risk":"high","permissions":["n8n instance (self-hosted or cloud)","ScrapingBee API key with active subscription","HTTP request node support in n8n (included in core)","Network connectivity to ScrapingBee cloud infrastructure","n8n instance with AI node support (OpenAI, Anthropic, or local LLM integration)","LLM API key (OpenAI, Anthropic, Hugging Face, or self-hosted model)","ScrapingBee API key for HTML retrieval","JSON schema definition for target data structure","n8n instance with loop/iterate node support","ScrapingBee API key with sufficient quota for batch size"],"failure_modes":["Browser rendering adds 2-5 second latency per request vs static HTML parsing","ScrapingBee API rate limits apply (typically 5,000-50,000 requests/month depending on plan)","No built-in JavaScript execution customization — limited to standard browser environment","Screenshot capture increases response payload size and API quota consumption","LLM parsing adds 1-3 second latency per request and increases API costs (LLM tokens + ScrapingBee)","Hallucination risk if pages contain ambiguous or missing data — requires validation nodes","Schema definition must be precise; vague field descriptions lead to inconsistent extraction","No built-in error recovery if LLM fails to parse — requires manual workflow branching","Sequential processing is slow for large lists (1000 URLs × 5 seconds = 83 minutes)","Parallel processing with high concurrency may hit ScrapingBee rate limits or trigger anti-bot detection","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.14214228596176343,"quality":0.47,"ecosystem":0.7000000000000001,"match_graph":0.25,"freshness":0.6,"weights":{"adoption":0.2,"quality":0.25,"ecosystem":0.1,"match_graph":0.4,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:22.063Z","last_scraped_at":"2026-05-03T13:59:57.743Z","last_commit":"2026-03-12T14:29:03Z"},"community":{"stars":167,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=scrapingbee--n8n-no-code-web-scraper","compare_url":"https://unfragile.ai/compare?artifact=scrapingbee--n8n-no-code-web-scraper"}},"signature":"907dHZiBbZrZ90JjRxq+p4XVo7OAIIYyAXK4NNaUb499nLcNvcWyxfTts3//MZuIm3Ic4o45TaceWF0aoMdcCg==","signedAt":"2026-06-19T18:20:05.137Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/scrapingbee--n8n-no-code-web-scraper","artifact":"https://unfragile.ai/scrapingbee--n8n-no-code-web-scraper","verify":"https://unfragile.ai/api/v1/verify?slug=scrapingbee--n8n-no-code-web-scraper","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}