| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 10 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes Bright Data's web scraping infrastructure through the Model Context Protocol, allowing LLM agents and tools to request structured data extraction from websites without managing proxies, browsers, or anti-bot handling directly. Implements MCP server pattern that translates tool-calling requests into Bright Data API calls, handling authentication, session management, and response parsing transparently.
Unique: Bridges Bright Data's managed scraping infrastructure (proxy rotation, anti-bot handling, browser rendering) directly into LLM tool-calling via MCP, eliminating the need for agents to manage scraping complexity themselves — the MCP server acts as a stateless adapter translating semantic scraping requests into optimized Bright Data API calls.
vs alternatives: Unlike generic web scraping libraries (Puppeteer, Cheerio) that require agents to handle proxies and anti-bot detection, this MCP integration delegates infrastructure concerns to Bright Data's managed service, allowing LLMs to focus on data interpretation rather than scraping mechanics.
Abstracts Bright Data's residential and datacenter proxy networks behind MCP tool calls, allowing LLM agents to request data from geographically-specific or IP-rotated contexts without managing proxy pools, authentication, or rotation logic. The MCP server handles proxy selection, failover, and session persistence transparently, presenting a simple semantic interface to the agent.
Unique: Encapsulates Bright Data's proxy selection logic (residential pool, datacenter, ISP, sticky sessions) as MCP tools, allowing agents to request 'data from Japan' or 'rotate IP every request' as semantic operations rather than managing proxy configuration — the server handles pool selection, failover, and session affinity internally.
vs alternatives: Compared to agents managing raw proxy APIs or local proxy software, this MCP abstraction eliminates configuration complexity and provides Bright Data's managed residential proxy quality (higher success rates, better geo-coverage) while keeping agent code focused on data logic.
Provides MCP tool interface to Bright Data's residential IP pool, enabling agents to request data through specific IP addresses, sticky sessions, or rotating residential proxies without managing pool state locally. Implements session affinity tracking, IP rotation scheduling, and fallback logic server-side, exposing only high-level session and rotation controls to the agent.
Unique: Manages Bright Data's residential IP pool lifecycle (session creation, sticky routing, rotation scheduling, failover) as MCP server state, exposing only semantic session operations to agents — agents request 'create sticky session for 20 minutes' rather than managing IP lists or rotation timers.
vs alternatives: Unlike agents managing raw proxy lists or local proxy software, this MCP integration provides Bright Data's managed residential quality with automatic failover, geographic diversity, and session persistence — agents get reliable residential IP behavior without infrastructure overhead.
Exposes Bright Data's datacenter proxy network through MCP tools, allowing agents to route requests through high-speed datacenter IPs for performance-critical or high-volume data collection. Implements connection pooling, load balancing, and automatic failover server-side, with MCP interface for proxy selection by country, ISP, or performance tier.
Unique: Abstracts Bright Data's datacenter proxy pool with server-side load balancing and failover, allowing agents to request 'fast data fetch from US datacenter pool' without managing individual proxy endpoints — the MCP server handles connection pooling and automatic IP rotation within the datacenter tier.
vs alternatives: Compared to agents managing raw datacenter proxy lists, this MCP integration provides automatic load balancing, failover, and performance optimization — agents get consistent fast performance without proxy management overhead.
Integrates Bright Data's anti-bot detection evasion capabilities (browser fingerprinting, header spoofing, CAPTCHA solving) through MCP tools, allowing agents to request data from protected sites without implementing evasion logic themselves. The MCP server handles browser emulation, header rotation, and CAPTCHA detection/solving transparently, presenting a simple 'fetch URL' interface to the agent.
Unique: Encapsulates Bright Data's anti-bot detection evasion (browser fingerprinting, header spoofing, CAPTCHA solving via third-party services) as a single MCP tool, allowing agents to request 'fetch protected URL' without understanding evasion mechanics — the server handles detection, evasion strategy selection, and CAPTCHA solving internally.
vs alternatives: Unlike agents implementing custom anti-bot evasion or managing Selenium/Puppeteer with proxy rotation, this MCP integration leverages Bright Data's managed anti-bot service with higher success rates and automatic strategy updates — agents get reliable protected-site access without evasion code.
Provides MCP tools for requesting structured data extraction from web content using schema-based selectors and validation, allowing agents to specify expected output structure (JSON schema) and receive validated, typed data. Implements server-side extraction using CSS selectors, XPath, or Bright Data's AI-powered extraction, with schema validation and type coercion before returning to agent.
Unique: Combines Bright Data's web scraping with server-side schema validation and type coercion, allowing agents to request 'extract product data matching this JSON schema' and receive guaranteed valid output — the MCP server handles extraction, validation, and error recovery without agent involvement.
vs alternatives: Unlike agents implementing custom extraction and validation, this MCP integration provides Bright Data's extraction quality with built-in schema validation — agents get type-safe structured data without parsing boilerplate.
Implements the Model Context Protocol server specification, exposing Bright Data capabilities as standardized MCP tools that LLM clients (Claude, ChatGPT, local LLMs) can discover and invoke. Uses MCP's JSON-RPC transport layer, tool schema registration, and resource management patterns to bridge Bright Data's REST API into LLM-native tool-calling interfaces.
Unique: Implements the full MCP server specification (JSON-RPC transport, tool schema registration, resource management) to expose Bright Data as native LLM tools, allowing Claude and other MCP clients to discover and invoke Bright Data functions without custom integration code — the server handles protocol translation, authentication, and response formatting.
vs alternatives: Unlike custom API wrappers or plugin systems, the MCP server implementation provides standardized tool-calling that works across multiple LLM platforms (Claude, ChatGPT, local LLMs) — agents get consistent Bright Data access without platform-specific code.
Manages Bright Data API authentication and credential lifecycle through the MCP server, handling token refresh, credential rotation, and secure storage of API keys. Implements credential injection into Bright Data API calls without exposing keys to LLM clients, using environment variables or secure config files for credential storage.
Unique: Centralizes Bright Data credential management in the MCP server, preventing API keys from being exposed to LLM clients or agents — credentials are injected server-side into Bright Data API calls, with support for token refresh and rotation without client involvement.
vs alternatives: Unlike agents managing credentials directly or passing keys through LLM context, this server-side credential management prevents key exposure to untrusted LLM clients and enables credential rotation without agent code changes.
+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 @brightdata/mcp at 23/100.
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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