SerpAPI
AIReal-time API to retrieve and parse search engine results while handling proxies and captchas for you.
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Free Available
Starting from Free
Premium plans available
SerpAPI
AI
Real-time API to retrieve and parse search engine results while handling proxies and captchas for you.
-(0 Reviews)
Free Available
Starting from Free
Premium plans available
About SerpAPI
SerpApi provides a real-time, hosted API to fetch search engine results and return structured data. It abstracts away proxy management and captcha solving, delivering parsed SERP features and rich structured results so developers can integrate search data without scraping infrastructure. Official client libraries and community SDKs (e.g., Python) simplify requests and parsing across multiple engines, enabling rapid integration into analytics, monitoring, and application workflows.
Key Features
Real-Time Search API: Provides immediate programmatic access to search engine results, returning parsed and structured data instead of raw HTML to simplify downstream processing.
Captcha Handling and Proxy Management: Automatically manages proxies and solves captchas on behalf of users to maintain reliable access to search engines without building custom anti-blocking infrastructure.
Rich Structured Data Parsing: Extracts SERP features and returns rich structured fields (such as snippets, knowledge panels, ads, local packs), reducing the need for custom parsers.
Multi-Engine Client Libraries: Official and community client libraries (e.g., python google-search-results package on GitHub) enable seamless integration with popular languages and frameworks.
Multi-Engine Support: Capable of querying multiple search engines and verticals (references include Google, Bing, Baidu, Yandex, Yahoo, major retail sites) through the same API interface.
Managed Scaling and Pagination: Handles paging, rate considerations, and result normalization so applications can request large volumes of SERP data reliably.
Integration with LLM Tooling: Usable as a web-search tool in frameworks such as LangChain to provide up-to-date search results for language model agents and workflows.
Real-time API access to Google search results
Handles proxies and proxy management to reduce blocking
Automatically solves or bypasses CAPTCHAs
Parses and returns rich structured search result data (JSON)
Supports multiple search engines and verticals (Google, Bing, Baidu, Yandex, Yahoo, Home Depot, eBay, etc.)
Official client libraries (e.g., google-search-results-python)
Open-source repositories on GitHub for SDKs and examples
Integrations/wrappers for tooling ecosystems (e.g., LangChain)
Designed to handle blocking/unblocking and other scraping-specific challenges
Use Cases
SEO Monitoring: Automatically track keyword rankings, SERP feature presence, and competitor results by fetching structured search results on schedule.
Market Intelligence and Price Comparison: Aggregate product search results across retail search engines to compare pricing, availability, and listings.
Content Aggregation and Research: Retrieve and normalize snippets, rich answers, and knowledge panels for content research or automated summarization workflows.
SERP Feature Extraction for Analytics: Extract and monitor SERP features (ads, local packs, featured snippets) for analytics dashboards or A/B testing visibility.
LLM-Augmented Web Search: Provide live web search results to language models or agents (e.g., LangChain integrations) to improve relevance and grounding.
Competitive Monitoring and Alerts: Build systems that detect changes in competitor visibility or ad placements by polling and diffing structured SERP data.
Web scraping of search engine result pages (SERP) for structured data extraction
SEO monitoring and analytics using live search results
Building search-driven applications and agents via LangChain or other frameworks
E-commerce search and price comparison across marketplaces
Research and competitive intelligence that require parsed SERP data
Screenshots
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