| 0 |
| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 13 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Extracts structured data from a single web page using semantic AI understanding rather than CSS selectors or XPath. The AiScraper client sends a URL and natural language prompt to the Oxylabs API, which uses vision and language models to understand page semantics, locate relevant content, and return structured JSON matching the requested schema. This approach is resilient to DOM changes because it operates on semantic meaning rather than brittle selectors.
Unique: Uses vision-language models to understand page semantics and extract data based on meaning rather than DOM structure, making it resilient to HTML changes that would break traditional CSS/XPath selectors. The SDK abstracts job polling and retry logic, exposing a simple scrape() method that handles async API communication internally.
vs alternatives: More resilient to website structure changes than Puppeteer/Selenium + regex, and requires no selector maintenance compared to BeautifulSoup or Scrapy, though with higher latency due to remote AI processing.
Discovers and extracts data from multiple related pages across a website using AI-driven navigation. The AiCrawler client accepts a starting URL and a natural language prompt describing which pages to visit (e.g., 'follow all product links and extract prices'), then uses semantic understanding to identify relevant links, navigate to them, and extract data from each page. The SDK manages job polling and pagination internally, returning aggregated results from all discovered pages.
Unique: Uses semantic understanding to identify which links to follow based on natural language intent, rather than requiring hardcoded URL patterns or CSS selectors. The SDK's job polling pattern abstracts the asynchronous crawl lifecycle, allowing developers to write synchronous code that internally manages long-running API operations.
vs alternatives: Eliminates the need for custom link-following logic compared to Scrapy or Selenium, and adapts to website structure changes automatically because navigation is semantic rather than pattern-based. Slower than headless browser crawlers but requires no JavaScript rendering overhead.
Supports multiple output formats for extracted data, including JSON, HTML, CSV, and raw text. The SDK allows developers to specify desired output format per request, and handles serialization and formatting automatically. This capability enables integration with downstream tools and databases that expect specific formats without requiring post-processing.
Unique: Provides flexible output format options integrated into the extraction pipeline, allowing developers to specify format at request time without post-processing. The SDK handles serialization automatically based on format selection.
vs alternatives: More convenient than post-processing extraction results to convert formats, and supports multiple formats without additional dependencies. Limited to formats supported by the SDK.
Provides comprehensive error handling with detailed diagnostics for extraction failures, including retry logic for transient errors, timeout handling, and structured error messages. The SDK distinguishes between transient errors (network timeouts, temporary API unavailability) and permanent errors (invalid input, authentication failure), applying appropriate retry strategies. Error responses include detailed context (which step failed, why, what was attempted) to aid debugging.
Unique: Integrates error handling and retry logic into the SDK's job polling pattern, automatically retrying transient failures with exponential backoff while providing detailed diagnostics for permanent failures. Distinguishes between error types to apply appropriate recovery strategies.
vs alternatives: More integrated than manual retry logic and provides better diagnostics than generic HTTP error handling. Automatic retry reduces boilerplate code compared to implementing custom retry decorators.
Tracks API usage and enforces rate limits to prevent quota exhaustion. The SDK monitors the number of requests made and remaining quota, and can throttle requests to stay within rate limits. It provides usage statistics and quota warnings to help developers understand their consumption patterns and avoid unexpected quota overages.
Unique: Integrates rate limiting and quota tracking into the SDK's request pipeline, providing automatic throttling and usage statistics without requiring external monitoring tools. The SDK tracks quota consumption and warns developers when approaching limits.
vs alternatives: More integrated than manual quota tracking and provides automatic throttling without external rate limiting services. Depends on accurate quota information from the Oxylabs API.
Automates complex browser interactions (clicking, form filling, navigation, waiting) using high-level natural language instructions instead of imperative code. The BrowserAgent client accepts a starting URL and an action prompt (e.g., 'log in with email, search for laptops, sort by price'), then uses AI to interpret the prompt, execute the sequence of browser actions, and return the final page state or extracted data. The SDK handles browser session management, JavaScript rendering, and action execution remotely.
Unique: Interprets natural language action sequences using AI models rather than requiring imperative Selenium/Playwright code, making it accessible to non-programmers. The SDK manages remote browser session lifecycle and JavaScript rendering, abstracting away the complexity of headless browser control.
vs alternatives: More intuitive than Selenium for non-technical users and requires no knowledge of DOM selectors or browser APIs. Slower than local Playwright due to remote execution, but eliminates the need to maintain browser automation code as websites change.
Performs web searches and retrieves content from search results using semantic filtering and AI-powered extraction. The AiSearch client accepts a search query and optional filters (e.g., 'find articles about AI safety published in the last month'), then returns a list of search results with extracted content from each page. The SDK handles search engine integration, result ranking, and per-result content extraction internally.
Unique: Combines web search with AI-powered content extraction from results, allowing developers to retrieve and structure data from search results in a single operation. The SDK abstracts search engine integration and per-result extraction, exposing a unified search() method.
vs alternatives: More integrated than using Google Search API + separate scraping tools, and provides structured extraction from results without additional parsing steps. Slower than direct search APIs but includes automatic content extraction.
Analyzes a website's structure to discover page hierarchies, relationships, and navigation patterns using semantic understanding. The AiMap client accepts a starting URL and returns a map of the site's structure, including discovered pages, their relationships, and navigation paths. This capability uses AI to understand site semantics (e.g., 'this is a product category page, these are product detail pages') rather than relying on URL patterns or sitemap files.
Unique: Uses semantic AI to classify page types and understand site structure based on content meaning rather than URL patterns or sitemap files, enabling discovery of sites without explicit navigation metadata. The SDK returns structured hierarchy data suitable for downstream crawling or analysis.
vs alternatives: More intelligent than URL pattern-based site mapping and does not require sitemap.xml files. Slower than parsing sitemaps but works on sites without explicit navigation metadata.
+5 more capabilities
Executes SQL queries against Supabase PostgreSQL instances through the Model Context Protocol, translating natural language or structured query requests into parameterized SQL statements. Uses MCP's tool-calling interface to expose database operations as callable functions with schema validation, enabling LLM agents to perform CRUD operations, joins, and aggregations with automatic connection pooling and credential management through Supabase client SDK.
Unique: Exposes Supabase PostgreSQL as MCP tools with automatic credential injection from Supabase client SDK, eliminating manual connection string management and enabling seamless LLM-to-database queries within Claude or compatible agents
vs alternatives: Tighter integration than generic SQL MCP servers because it leverages Supabase's built-in authentication and connection pooling rather than requiring separate database credential configuration
Exposes Supabase Auth session state and user metadata through MCP tools, allowing agents to inspect current authentication context, retrieve user profiles, and trigger auth-related operations. Integrates with Supabase's JWT-based auth system to validate sessions and access user claims without re-authenticating, using the Supabase client's built-in session management.
Unique: Integrates Supabase's JWT-based auth system directly into MCP tool interface, allowing agents to inspect and act on auth state without managing separate credential stores or re-authentication flows
vs alternatives: More seamless than generic auth MCP servers because it leverages Supabase's built-in session management and avoids redundant credential passing between agent and auth system
Invokes Supabase Edge Functions (serverless TypeScript/JavaScript functions) through MCP tools, passing parameters and receiving results with optional streaming support. Uses Supabase's edge function HTTP API to trigger functions with automatic authentication headers and response parsing, enabling agents to execute custom business logic without embedding it in the agent itself.
Supabase scores higher at 42/100 vs oxylabs-ai-studio-py at 35/100.
Need something different?
Search the match graph →© 2026 Unfragile. Stronger through disorder.
Unique: Exposes Supabase Edge Functions as MCP tools with automatic authentication and response parsing, allowing agents to invoke custom serverless logic without managing HTTP clients or credential injection
vs alternatives: More integrated than generic HTTP MCP tools because it handles Supabase-specific authentication, error handling, and response formatting automatically
Subscribes to real-time changes on Supabase tables through MCP's event streaming interface, using Supabase's PostgreSQL LISTEN/NOTIFY mechanism to push INSERT, UPDATE, and DELETE events to agents. Maintains persistent WebSocket connections and filters events by table and row-level policies, enabling agents to react to database changes without polling.
Unique: Bridges Supabase's PostgreSQL LISTEN/NOTIFY real-time system with MCP's tool interface, enabling agents to subscribe to database changes without managing WebSocket connections or event serialization
vs alternatives: More efficient than polling-based approaches because it uses Supabase's native real-time infrastructure rather than repeated database queries
Manages files in Supabase Storage buckets through MCP tools, supporting upload, download, list, and delete operations with automatic authentication and path-based access control. Uses Supabase's S3-compatible storage API with built-in support for public/private buckets and signed URLs for temporary access, enabling agents to handle file I/O without managing cloud storage credentials.
Unique: Exposes Supabase Storage's S3-compatible API as MCP tools with automatic authentication and signed URL generation, eliminating the need for agents to manage cloud storage credentials or generate temporary access tokens
vs alternatives: More integrated than generic S3 MCP tools because it leverages Supabase's built-in bucket policies and authentication rather than requiring separate AWS credentials
Performs semantic similarity searches on vector embeddings stored in Supabase PostgreSQL using pgvector extension, translating natural language queries into embedding vectors and executing cosine/L2 distance searches. Integrates with embedding providers (OpenAI, Cohere) or uses pre-computed embeddings, enabling agents to retrieve semantically similar documents or records without full-text search limitations.
Unique: Integrates pgvector directly into MCP tools with automatic embedding generation and distance calculation, enabling agents to perform semantic search without managing separate vector database infrastructure
vs alternatives: More efficient than external vector databases (Pinecone, Weaviate) for Supabase users because it colocates embeddings with relational data, reducing network latency and simplifying data synchronization
Exposes Supabase database schema information through MCP tools, allowing agents to discover table structures, column types, constraints, and relationships without manual schema documentation. Queries PostgreSQL information_schema and Supabase metadata tables to dynamically generate schema descriptions, enabling agents to construct valid queries and understand data relationships.
Unique: Queries Supabase's PostgreSQL information_schema directly through MCP tools, enabling agents to dynamically discover and adapt to database schemas without pre-configured schema definitions
vs alternatives: More flexible than static schema definitions because it reflects live database state, including recent migrations or schema changes
Enforces Supabase Row-Level Security policies within agent queries, ensuring that agents can only access rows permitted by RLS rules defined in the database. Evaluates policies based on authenticated user context (JWT claims, user ID) and applies WHERE clause filters automatically, preventing unauthorized data access at the database layer rather than application layer.
Unique: Delegates authorization enforcement to PostgreSQL RLS policies rather than implementing authorization in agent code, ensuring that data access rules are centralized and cannot be bypassed by agent logic
vs alternatives: More secure than application-level authorization because RLS is enforced at the database layer, preventing accidental data leaks even if agent code has bugs
+1 more capabilities