| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Starting Price | $50/mo | — |
| Capabilities | 17 decomposed | 12 decomposed |
| Times Matched | 0 | 0 |
Unified API that scrapes and structures organic search results from 10+ search engines (Google, Bing, Yahoo, DuckDuckGo, Yandex, Baidu, Naver, Brave) by routing requests through a distributed proxy network with automatic CAPTCHA solving and anti-bot detection evasion. Returns normalized JSON with result ranking, snippets, URLs, and metadata across heterogeneous SERP layouts.
Unique: Operates a proprietary distributed proxy network with integrated CAPTCHA solving (likely via third-party service like 2Captcha or internal ML model) and automatic retry logic, eliminating the need for consumers to manage anti-bot evasion infrastructure themselves. Normalizes heterogeneous SERP HTML structures into unified JSON schema across 10+ engines.
vs alternatives: Broader engine coverage (10+ vs competitors' 3-5) and built-in CAPTCHA handling reduce implementation complexity vs raw Selenium/Puppeteer scraping, though with higher per-request cost and latency variance
Dedicated endpoints for Google Images, Bing Images, Yahoo Images, Yandex Images, and Baidu Images that extract image URLs, thumbnails, source pages, and metadata (dimensions, alt text, license info) from image search results. Handles image-specific anti-scraping (image hotlink protection, dynamic loading) via proxy rotation and JavaScript rendering.
Unique: Reverse image search capability (Google Lens API, Google Reverse Image API) that accepts image URLs or base64-encoded image data and returns visually similar results with source attribution, implemented via integration with search engine reverse image endpoints rather than custom vision model.
vs alternatives: Unified API for 5+ image search engines vs building separate integrations; includes reverse image search without requiring custom ML model training
Built-in proxy rotation, CAPTCHA solving, and anti-bot detection evasion that transparently handles IP blocking, rate limiting, and bot detection challenges. Automatically retries failed requests with different proxy IPs and solves CAPTCHAs via third-party service or internal ML model.
Unique: Operates proprietary distributed proxy network with integrated CAPTCHA solving (likely via 2Captcha, hCaptcha, or internal ML model) and automatic retry logic with exponential backoff, eliminating need for consumers to manage anti-bot infrastructure.
vs alternatives: Transparent proxy/CAPTCHA handling vs manual Selenium/Puppeteer management; reduces implementation complexity but increases per-request cost
Supports geographic filtering by country, region, city, or coordinates to return localized search results. Automatically handles IP geolocation, language localization, and currency conversion for multi-region queries. Enables location-specific ranking and local result prioritization.
Unique: Supports geographic filtering across 10+ search engines by routing requests through proxy IPs in target countries and normalizing localized result layouts, enabling multi-region search result comparison without manual proxy management.
vs alternatives: Unified multi-region API vs building separate proxy infrastructure per country; automatic language and currency localization
Parses and extracts structured data from search results including JSON-LD, microdata, and Open Graph metadata. Returns normalized structured data for products, articles, events, organizations, and other schema.org types embedded in search result pages.
Unique: Automatically detects and extracts schema.org structured data (JSON-LD, microdata) embedded in search result HTML and normalizes into consistent JSON schema, enabling structured data aggregation without custom parsing logic per website.
vs alternatives: Automatic schema.org extraction vs manual HTML parsing; supports multiple schema markup formats (JSON-LD, microdata, RDFa)
Normalizes heterogeneous search engine HTML responses into consistent JSON schema across all endpoints. Implements domain-specific parsers for each vertical (e.g., flight prices, hotel ratings, product reviews) that extract structured fields from unstructured SERP markup. Handles schema variations across search engines and result types.
Unique: Implements domain-specific parsers for 50+ verticals (flights, hotels, shopping, finance, etc.) that extract structured fields from SERP markup, whereas generic SERP APIs return raw HTML or unstructured JSON
vs alternatives: Eliminates need for custom HTML parsing and schema normalization by providing pre-parsed JSON with consistent field names across search engines and verticals
Provides native SDKs for 11 programming languages (Python, JavaScript, Ruby, Go, PHP, Java, Rust, .NET, Swift, C++, and MCP) that wrap the HTTP API with language-specific abstractions, error handling, and type safety. SDKs handle authentication, request/response serialization, and rate limit management. MCP (Model Context Protocol) integration enables use as a tool within AI agents and LLM applications. Eliminates need for manual HTTP client setup and provides consistent API experience across languages.
Unique: Provides native SDKs for 11 languages with MCP (Model Context Protocol) support for AI agent integration, eliminating manual HTTP client setup and enabling seamless tool use in LLM applications. Handles authentication, serialization, and rate limiting transparently.
vs alternatives: More convenient than raw HTTP requests and avoids SDK fragmentation; MCP integration enables direct use in AI agents without custom wrapper code.
Automatically detects and solves CAPTCHAs encountered during search result scraping, using distributed proxy infrastructure to rotate IPs and evade rate limiting. Handles Google reCAPTCHA, hCaptcha, and other common CAPTCHA types. Transparently retries failed requests with different proxies and CAPTCHA solving services. Eliminates need for developers to implement custom CAPTCHA solving or proxy rotation logic.
Unique: Transparently handles CAPTCHA solving and proxy rotation without requiring developer intervention or separate CAPTCHA solving service credentials. Automatically retries failed requests with different proxies to maintain result availability at scale.
vs alternatives: Avoids need to integrate separate CAPTCHA solving services (2Captcha, Anti-Captcha) or manage proxy networks; simpler than building custom retry logic and proxy rotation.
+9 more capabilities
Store and automatically index high-dimensional vector embeddings in a managed, scalable database without manual infrastructure provisioning. The system handles index optimization and partitioning transparently.
Query stored vectors to find semantically similar items by computing distance metrics between query embeddings and indexed vectors. Returns ranked results based on relevance in sub-100ms latency.
Serve as the retrieval component in Retrieval-Augmented Generation pipelines, providing relevant context documents to language models for grounded responses.
Provide a generous free tier (1 pod, 100K vectors) enabling teams to build and test real applications before committing to paid plans.
Execute searches using both dense vector embeddings and sparse keyword-based vectors simultaneously, combining results to improve relevance by capturing both semantic and lexical similarity.
Filter vector search results based on metadata attributes (tags, categories, timestamps, custom fields) before or during similarity search, enabling faceted and conditional retrieval.
Insert, update, or replace multiple vectors and their metadata in a single batch operation, optimizing throughput for bulk data ingestion without individual API calls.
Pinecone scores higher at 71/100 vs SerpAPI at 56/100. SerpAPI leads on adoption, while Pinecone is stronger on quality.
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Partition vector data within a single index using namespaces, enabling logical separation of data (by user, tenant, or dataset) without creating separate indexes.
+4 more capabilities