| 0 |
| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
This capability allows the agent to autonomously capture screenshots and analyze the structure of web pages using Playwright's browser automation. It leverages a combination of DOM inspection and visual rendering to identify interactive elements and their states, enabling it to provide insights into UI bugs and layout issues. The integration with Playwright allows for cross-browser support, making it versatile across different environments.
Unique: Utilizes Playwright's advanced rendering capabilities to analyze web pages without needing native vision, making it accessible for various AI models.
vs alternatives: More comprehensive than traditional screenshot tools as it combines visual analysis with interactive element mapping.
This capability enables the agent to simulate user interactions by navigating through a web application, filling out forms, and validating workflows. It captures each step with screenshots and logs, allowing developers to see where a workflow might fail. The agent uses Playwright's API to perform these actions programmatically, ensuring consistent testing across different scenarios.
Unique: Combines visual validation with automated interaction, allowing for a complete overview of user journeys in a single tool.
vs alternatives: More detailed than standard UI testing tools because it captures the entire workflow with visual evidence.
This capability measures web application performance metrics such as load times and Core Web Vitals. It uses Playwright's built-in performance monitoring tools to gather data during page loads and interactions, providing insights into potential bottlenecks. The agent can log these metrics in real-time, allowing for immediate feedback on performance issues.
Unique: Integrates real-time performance monitoring with visual testing, providing a holistic view of both functionality and speed.
vs alternatives: Offers deeper insights than traditional performance tools by combining visual testing with performance metrics.
This capability allows the agent to validate backend API responses by sending requests and checking the responses against expected outcomes. It uses Playwright's API testing capabilities to simulate requests and log results, ensuring that the frontend and backend are in sync. This feature is essential for full-stack testing and can be integrated into CI/CD pipelines.
Unique: Combines API testing with visual UI testing, allowing for comprehensive validation of both frontend and backend interactions.
vs alternatives: More integrated than standalone API testing tools, as it allows simultaneous UI and API validation.
This capability highlights visual differences between two versions of a web page by capturing screenshots of both states and analyzing them for discrepancies. It uses image processing techniques to detect changes in layout, color, and content, providing a clear report of what has changed. This is particularly useful for regression testing and ensuring design consistency.
Unique: Utilizes advanced image processing to provide detailed visual comparisons, making it easier to spot regressions than traditional pixel comparison tools.
vs alternatives: More effective than basic screenshot comparison tools due to its ability to analyze and report on specific UI changes.
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 visual-ui-debug-agent-mcp at 32/100.
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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