| 0 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 12 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes BrowserStack's cloud browser infrastructure as MCP tools, allowing Claude and other MCP clients to spawn, control, and terminate remote browser sessions across 2000+ device/OS/browser combinations. Implements the Model Context Protocol as a server that translates high-level browser automation intents into BrowserStack REST API calls, managing session lifecycle, capabilities negotiation, and result streaming back to the client.
Unique: First official MCP server from BrowserStack that bridges Claude/MCP clients directly to real device cloud infrastructure; implements MCP tool schema for 2000+ device combinations without requiring developers to write Selenium/WebDriver code
vs alternatives: Tighter integration than generic Selenium MCP wrappers because it's BrowserStack-native, with pre-built device capability definitions and optimized session management for the cloud platform
Provides MCP tools to query and filter BrowserStack's device catalog (2000+ combinations of browsers, OS versions, devices, screen resolutions). Implements server-side filtering logic that translates human-readable device queries ('latest Chrome on iPhone 15') into BrowserStack capability objects, with caching of the device list to reduce API calls.
Unique: Exposes BrowserStack's internal device taxonomy as queryable MCP tools, allowing agents to dynamically construct test matrices without hardcoding device strings; includes intelligent filtering for common patterns like 'latest browsers' or 'flagship devices'
vs alternatives: More discoverable than raw BrowserStack API because it's wrapped as MCP tools with natural filtering; better than static device lists because it stays in sync with BrowserStack's catalog
Collects performance metrics (Core Web Vitals, load time, resource timing, memory usage) from remote sessions and provides MCP tools to analyze and compare performance across devices. Implements metric collection via WebDriver performance APIs and optional integration with BrowserStack's performance monitoring, with result aggregation and trend analysis.
Unique: Collects and aggregates performance metrics from remote BrowserStack sessions, enabling systematic performance monitoring across devices; includes comparison and trend analysis for regression detection
vs alternatives: More comprehensive than local performance testing because it measures on real devices with real network conditions; better than manual performance review because it's automated and quantified
Captures browser console logs, JavaScript errors, network requests, and other debugging information from remote sessions. Implements log streaming via WebDriver protocol, with filtering and categorization of errors by type (JS errors, network failures, security warnings). Includes optional integration with error tracking services (Sentry, LogRocket) for centralized error analysis.
Unique: Streams debugging information from remote BrowserStack sessions as MCP tool outputs, allowing agents to capture and analyze errors without manual log inspection; includes filtering and categorization for easier debugging
vs alternatives: More accessible than browser DevTools because logs are returned as structured data; better than manual error reproduction because it captures errors automatically during test execution
Enables remote screenshot capture from BrowserStack sessions and returns image data (base64 or URL) that can be piped into Claude's vision capabilities or external image comparison tools. Implements screenshot buffering and optional compression to manage payload sizes when sending images back through MCP protocol.
Unique: Integrates screenshot capture with MCP protocol, allowing Claude to directly analyze visual output from remote browsers; supports both base64 embedding and URL references for flexible image handling
vs alternatives: More seamless than manual screenshot downloads because images are returned as MCP tool outputs that Claude can immediately process; better than local Selenium screenshots for cross-device testing since it captures real device rendering
Provides MCP tools to execute arbitrary JavaScript in the context of a remote BrowserStack session and retrieve DOM state, computed styles, or custom script results. Implements script injection via WebDriver protocol, with result serialization and error handling for non-serializable objects (functions, DOM nodes are converted to string representations).
Unique: Exposes WebDriver executeScript capability as an MCP tool, allowing Claude to generate and run custom JavaScript in remote sessions without writing WebDriver code; includes automatic result serialization for complex objects
vs alternatives: More flexible than pre-built interaction tools because it allows arbitrary script execution; safer than direct WebDriver access because it's wrapped in MCP protocol with error handling
Manages the lifecycle of BrowserStack sessions (creation, tracking, termination) with automatic cleanup on session end. Implements session ID tracking, timeout handling, and resource deallocation to prevent orphaned sessions that consume BrowserStack concurrency limits. Includes optional session persistence metadata for debugging and audit trails.
Unique: Implements MCP-aware session lifecycle management that integrates with the protocol's tool invocation model; tracks sessions at the MCP server level to ensure cleanup even if client disconnects unexpectedly
vs alternatives: Better resource safety than raw BrowserStack API because the MCP server enforces cleanup hooks; more reliable than client-side cleanup because it's centralized in the server process
Allows MCP clients to spawn and coordinate multiple concurrent BrowserStack sessions, with built-in concurrency limiting to respect BrowserStack account limits. Implements a session queue and rate limiter that prevents exceeding the account's concurrent session cap, with optional load balancing across regions if available.
Unique: Implements MCP-level concurrency management that abstracts BrowserStack's session limits, allowing agents to request parallel sessions without manually managing queue logic; includes rate limiting to prevent quota exhaustion
vs alternatives: Simpler than building custom queue logic because concurrency is handled transparently by the MCP server; safer than direct API calls because it enforces account-level limits
+4 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 @browserstack/mcp-server at 34/100.
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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