| 0 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 12 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Executes JavaScript code in a real Chrome/Chromium browser context through the Chrome DevTools Protocol (CDP), with built-in anti-detection mechanisms to evade bot-detection scripts. Implements stealth headers, user-agent spoofing, and WebDriver property masking to appear as legitimate browser traffic rather than automated tooling. Rebuilt from chrome-devtools-mcp architecture to optimize for AI agent workflows.
Unique: Integrates anti-detection evasion directly into MCP server layer (stealth headers, WebDriver masking, user-agent rotation) rather than requiring separate proxy/VPN setup, enabling AI agents to handle detection-aware scraping natively without external infrastructure
vs alternatives: Differs from Puppeteer/Playwright by bundling anti-detection as first-class concern in MCP protocol, vs requiring manual stealth plugin configuration; more agent-friendly than raw CDP clients because it abstracts detection complexity into tool definitions
Automatically generates Model Context Protocol (MCP) tool definitions from browser capabilities, exposing Chrome DevTools operations as callable functions with strict JSON schemas. Handles parameter validation, return type serialization, and error mapping to MCP protocol standards. Enables AI agents to discover and invoke browser operations through standard MCP tool-calling interface without manual schema authoring.
Unique: Generates MCP tool schemas specifically optimized for agent workflows (with clear intent descriptions, parameter constraints, and error handling) rather than generic CDP method exposure, making browser operations first-class agent capabilities
vs alternatives: More agent-native than raw CDP clients or Puppeteer because it abstracts browser operations into MCP tool protocol, enabling multi-step agent reasoning about browser tasks vs imperative script execution
Implements automatic retry logic for transient failures (network timeouts, element not found, navigation failures) with exponential backoff. Provides detailed error context (error type, stack trace, recovery action) for agent decision-making. Supports custom retry predicates for domain-specific failure handling. Distinguishes between recoverable and fatal errors.
Unique: Provides agent-native error handling with automatic retry and exponential backoff, vs raw CDP which fails immediately on transient errors requiring agents to implement retry logic
vs alternatives: More resilient than Puppeteer's default error handling because it automatically retries transient failures with configurable backoff; enables agents to focus on logic vs error recovery
Tracks browser performance metrics (page load time, JavaScript execution time, network latency) and resource usage (memory, CPU, network bandwidth). Provides performance data in structured format for agent analysis. Enables agents to make performance-aware decisions (skip slow pages, optimize workflows). Supports performance budgets and alerts.
Unique: Provides agent-native performance monitoring with structured metrics and budget tracking, enabling agents to optimize workflows based on performance data; vs raw CDP which requires agents to manually collect and analyze performance metrics
vs alternatives: More agent-friendly than manual CDP performance API calls because it aggregates metrics and provides structured output; enables performance-aware agent decisions vs blind optimization
Executes arbitrary JavaScript code within a real browser's JavaScript engine (V8 via Chrome), capturing return values, console output, and errors, then serializes results back to JSON for agent consumption. Handles async/await execution, Promise resolution, and complex object serialization. Provides execution timeout and memory limits to prevent runaway scripts from blocking the MCP server.
Unique: Executes code in real V8 engine (Chrome) rather than Node.js, capturing browser-specific APIs (DOM, fetch, localStorage) and rendering context; includes automatic serialization of results to JSON with timeout/memory guardrails for safe agent execution
vs alternatives: More faithful to real browser behavior than Node.js eval() because it uses actual Chrome V8 with DOM APIs; safer than raw eval() because it enforces execution timeouts and memory limits preventing agent-induced DoS
Provides high-level DOM query operations (select, find, filter) using CSS selectors, with built-in element interaction methods (click, type, scroll, hover). Abstracts low-level CDP commands into agent-friendly operations that return structured element metadata (text, attributes, position). Handles dynamic element waiting and stale element recovery.
Unique: Wraps CDP element interaction commands into agent-native tool definitions with automatic element waiting and stale element recovery, vs raw CDP which requires agents to handle timing and retry logic manually
vs alternatives: More agent-friendly than Puppeteer's page.$(selector) because it returns structured metadata and handles common failure modes (stale elements, visibility checks) automatically; simpler than raw CDP for agents unfamiliar with low-level browser protocol
Handles page navigation (goto, reload, back, forward) with configurable wait conditions (wait for load, network idle, specific elements). Tracks navigation history and page state, enabling agents to understand page transitions. Implements timeout handling for navigation failures and provides detailed navigation metadata (URL, title, load time).
Unique: Provides agent-friendly navigation abstraction with built-in wait condition handling (load, idle, element presence) and timeout management, vs raw CDP which requires agents to manually poll for page readiness
vs alternatives: Simpler than Puppeteer's page.goto() for agents because it abstracts wait condition complexity; more reliable than raw CDP navigation because it handles common failure modes (slow loads, redirects) with configurable timeouts
Captures full-page or viewport screenshots as base64-encoded PNG/JPEG, with optional element highlighting and annotation. Provides visual feedback for agent workflows, enabling agents to understand page layout and validate visual state. Supports viewport size configuration and device emulation for responsive testing.
Unique: Integrates screenshot capture as first-class MCP tool with element highlighting and viewport control, enabling agents to make visual decisions; vs raw CDP which returns raw image data without agent-friendly metadata
vs alternatives: More agent-native than Puppeteer screenshots because it provides structured metadata (element positions, viewport info) alongside image data; enables visual reasoning in agent chains vs text-only automation
+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 js-reverse-mcp at 33/100.
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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