| 0 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 14 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Launches and maintains a single persistent Playwright browser instance (Chromium, Firefox, or WebKit) across multiple MCP tool invocations, with automatic page context management and error recovery. The server implements a global browser state pattern where the browser instance persists until explicitly closed, enabling multi-step workflows where each tool call operates on the same page context without re-initialization overhead.
Unique: Implements MCP protocol binding for Playwright with a global browser singleton pattern, allowing LLMs to invoke 27 browser tools against a persistent page context without managing browser lifecycle — the server handles all browser state internally via BrowserToolBase inheritance and requestHandler.ts dispatch logic
vs alternatives: Simpler than Selenium Grid or Puppeteer clusters for LLM integration because it abstracts browser lifecycle entirely behind MCP tools, eliminating the need for agents to manage WebDriver sessions or connection pooling
Provides 8+ DOM interaction tools (click, fill, hover, drag, select, type, focus, blur) that use Playwright's selector engine to locate and manipulate elements. Each tool accepts CSS selectors, XPath, or Playwright's built-in locator strategies (role-based, text-based), validates element visibility and interactability before action, and returns detailed error messages if elements are not found or disabled.
Unique: Wraps Playwright's locator engine with MCP tool contracts, enabling LLMs to use role-based and text-based selectors (e.g., 'button with text Submit') instead of brittle CSS selectors, with built-in visibility and interactability validation via Playwright's isVisible() and isEnabled() checks before action execution
vs alternatives: More robust than raw Selenium WebDriver for LLM use because Playwright's locator strategies (role, text, label) are more resilient to DOM changes, and the MCP abstraction eliminates the need for agents to manage WebDriver waits or exception handling
Provides playwright_fill, playwright_select, and playwright_check tools that handle form input, dropdown selection, and checkbox/radio button toggling. The tools use Playwright's fill() for text inputs, selectOption() for <select> elements, and check()/uncheck() for checkboxes and radio buttons. Each tool validates element type before interaction and returns success/error status.
Unique: Provides separate MCP tools for fill, select, and check operations, each with element-type validation and error handling, enabling LLMs to interact with standard HTML forms without understanding the differences between input types or managing Playwright's type-specific APIs
vs alternatives: More robust than generic click-and-type automation because it uses Playwright's type-specific APIs (selectOption for dropdowns, check for checkboxes) which handle browser quirks and validation, reducing flakiness compared to simulating clicks and keyboard input
Provides playwright_switch_frame and playwright_get_frames tools that manage frame and iframe context switching. The tools use Playwright's frame() API to select frames by name, URL, or index, and return frame information (name, URL, parent frame). Enables automation of pages with iframes, nested frames, and cross-origin frames (if allowed by CORS).
Unique: Exposes Playwright's frame() API as MCP tools for frame switching and enumeration, enabling LLMs to navigate iframe hierarchies without understanding Playwright's frame context model or managing frame references across tool invocations
vs alternatives: More explicit than Selenium's frame switching because it provides frame enumeration (get_frames) and returns frame metadata (name, URL), allowing agents to discover frames dynamically rather than hardcoding frame selectors
Provides expect_response and assert_response tools that validate HTTP responses from API calls or page navigation. The tools check response status codes, headers, body content (JSON schema, text patterns), and return validation results (pass/fail) with detailed error messages. Useful for verifying API contracts and detecting unexpected responses during automation.
Unique: Provides dedicated assertion tools (expect_response, assert_response) that validate HTTP responses with structured error reporting, enabling LLMs to verify API contracts and detect errors without writing custom validation logic or parsing response objects
vs alternatives: More integrated than generic assertion libraries because it works directly with MCP tool responses and provides structured validation results that agents can reason about, rather than requiring agents to parse response objects and write custom validation code
Provides playwright_screenshot and playwright_save_as_pdf tools that capture page visuals in PNG or PDF format with optional viewport and full-page rendering. The tools accept options for full-page capture, viewport dimensions, clip regions, and quality settings. Screenshots are returned as base64-encoded PNG, and PDFs are returned as binary files. Useful for visual testing, documentation, and evidence collection.
Unique: Exposes Playwright's screenshot() and pdf() APIs as MCP tools with base64 encoding for easy transport over STDIO, enabling LLMs to capture visual evidence without managing file I/O or image encoding, and returning images directly in tool responses for agent reasoning
vs alternatives: More convenient than raw Playwright screenshots because it returns base64-encoded images directly in MCP tool responses, allowing LLMs to reason about visual content without requiring separate file handling or image transport mechanisms
Extracts visible text, HTML structure, and accessibility tree from the current page via playwright_get_visible_text and playwright_get_page_content tools, and captures full-page or viewport screenshots as PNG/PDF via playwright_screenshot and playwright_save_as_pdf. The extraction logic uses Playwright's textContent() and innerHTML() APIs with optional filtering to return only visible, non-hidden elements.
Unique: Combines Playwright's textContent(), innerHTML(), and accessibility tree APIs into MCP tools that return structured data (text, HTML, ARIA tree) alongside visual captures (PNG, PDF), enabling LLMs to reason about page state using both textual and visual information without requiring separate vision models
vs alternatives: More comprehensive than Puppeteer's screenshot-only approach because it extracts both visual (PNG/PDF) and semantic (text, HTML, accessibility tree) representations, allowing agents to understand page structure without vision model overhead
Provides playwright_navigate, playwright_go_back, playwright_go_forward, and playwright_reload tools that control page navigation using Playwright's page.goto(), page.goBack(), page.goForward(), and page.reload() APIs. Each tool accepts URLs, handles redirects and timeouts, and returns navigation status (success, timeout, network error) with optional wait-for-load-state configuration (load, domcontentloaded, networkidle).
Unique: Wraps Playwright's navigation APIs with MCP tool contracts that expose wait-until strategies (load, domcontentloaded, networkidle) as tool parameters, allowing LLMs to specify load-state expectations without understanding Playwright internals, and returns structured navigation status (success/timeout/error) for agent decision-making
vs alternatives: More flexible than Selenium's WebDriver.get() because Playwright's wait-until strategies (networkidle) detect when dynamic content has finished loading, not just when DOM is ready, reducing flaky waits in AJAX-heavy applications
+6 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 mcp-playwright at 35/100.
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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