| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 10 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Captures complete website snapshots using Playwright's browser automation engine, extracting the full accessibility tree (DOM structure with ARIA labels, roles, and semantic information) alongside rendered visual state. The server launches headless browser instances, navigates to target URLs, waits for page stabilization, and serializes the accessibility tree into a structured format that LLMs can reason about without requiring visual rendering.
Unique: Focuses on accessibility tree extraction rather than screenshots, enabling LLMs to understand page semantics through ARIA roles and labels; integrates directly with Playwright's accessibility snapshot API to provide structured, machine-readable page representations
vs alternatives: More semantically rich than screenshot-based approaches (Puppeteer screenshots, Selenium screenshots) because it provides structured accessibility data that LLMs can directly reason about without requiring vision models
Intercepts and logs all HTTP/HTTPS network requests made during page load using Playwright's network interception API, collecting request/response metadata (URLs, headers, status codes, timing) into HAR (HTTP Archive) format. Enables analysis of API calls, resource loading patterns, and network performance without requiring manual request inspection or proxy configuration.
Unique: Leverages Playwright's native network interception to collect HAR logs without proxy configuration, providing LLMs with structured network activity data for API discovery and integration
vs alternatives: Simpler than proxy-based approaches (Fiddler, Charles) because it requires no external tools or certificate installation; more complete than browser DevTools export because it captures all requests programmatically
Collects all console output (console.log, console.error, console.warn, console.info) and JavaScript errors/exceptions that occur during page load and interaction. Messages are timestamped and categorized by severity level, enabling LLMs to detect runtime errors, warnings, and debug information that indicate page health or functionality issues.
Unique: Integrates Playwright's 'console' and 'pageerror' event handlers to provide structured, categorized console output to LLMs, enabling error detection without manual log inspection
vs alternatives: More accessible than browser DevTools console because it's programmatically captured and structured; more reliable than parsing HTML error messages because it captures actual runtime errors
Implements the Model Context Protocol (MCP) server specification, registering website snapshot capabilities as callable tools that Claude and other MCP-compatible LLMs can invoke directly. Uses MCP's JSON-RPC transport layer to expose snapshot, network monitoring, and console logging functions with standardized schema definitions, enabling seamless integration into LLM agent workflows without custom API wrappers.
Unique: Implements full MCP server specification with standardized tool schemas, allowing Claude and other MCP clients to invoke web automation capabilities as first-class tools without custom API integration
vs alternatives: More standardized than custom REST APIs because it uses MCP's schema-based tool definition; more integrated than function calling because it's native to Claude Desktop and other MCP hosts
Implements intelligent page load detection by waiting for network idle state (no pending network requests for a configurable duration) and optionally waiting for specific DOM elements to appear. Uses Playwright's built-in waitForLoadState() and waitForSelector() APIs to ensure pages are fully rendered before capturing snapshots, preventing incomplete or partial captures of dynamically-loaded content.
Unique: Combines Playwright's waitForLoadState('networkidle') with optional element selectors to provide flexible, multi-condition page readiness detection, enabling reliable snapshots of dynamic content
vs alternatives: More reliable than fixed-delay waits because it detects actual page readiness; more flexible than single-condition waits because it supports both network idle and DOM element conditions
Allows configuration of browser viewport dimensions and device emulation profiles (mobile, tablet, desktop) before capturing snapshots. Uses Playwright's device emulation to set user agent, viewport size, and device pixel ratio, enabling capture of responsive layouts and mobile-specific content variations without requiring multiple browser instances.
Unique: Leverages Playwright's built-in device emulation profiles to enable multi-device testing without managing separate browser instances, allowing LLMs to analyze responsive layouts
vs alternatives: More efficient than launching multiple browsers because it reuses browser context with different device profiles; more comprehensive than viewport-only changes because it includes user agent and device pixel ratio
Supports loading and saving browser cookies and session storage to enable authenticated access to websites. Allows pre-loading cookies from a file or configuration before navigation, and optionally persisting cookies after snapshot capture for reuse in subsequent requests. Enables automation of authenticated workflows without storing credentials directly.
Unique: Provides cookie-based session management without requiring credential storage, using Playwright's context.addCookies() API to enable authenticated access while maintaining security boundaries
vs alternatives: More secure than embedding credentials because it uses session cookies; more flexible than hardcoded login flows because it supports any authentication method that uses cookies
Allows injection of custom HTTP headers and user agent strings before making requests to websites. Uses Playwright's context.setExtraHTTPHeaders() to add custom headers (e.g., Authorization, X-Custom-Header) and device emulation to override user agent, enabling testing of header-dependent behavior and bypassing basic user agent detection.
Unique: Uses Playwright's context-level header injection to apply custom headers to all requests without modifying individual request handlers, enabling flexible header-based testing
vs alternatives: More convenient than request-level header manipulation because it applies globally; more reliable than user agent string manipulation in JavaScript because it's set at the browser context level
+2 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 Website Snapshot at 26/100.
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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