| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Paid | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Indexes and catalogs 28,999+ MCP servers in a searchable web interface organized by functional categories (Browser Automation, Cloud Platforms, Communication, etc.). Users query the registry by keyword, category, or browse curated collections to identify available MCP servers. The registry displays server metadata including creator, GitHub repository link, last update timestamp, and community star count to help developers evaluate server maturity and adoption.
Unique: Centralizes discovery of community-contributed MCP servers in a single indexed catalog with 28,999+ entries organized by functional domain, whereas developers previously had to search GitHub or rely on word-of-mouth to find available servers
vs alternatives: Provides broader coverage of MCP ecosystem than GitHub search alone by aggregating servers across multiple creators and repositories in one discoverable interface
Organizes the MCP server registry into functional categories (Browser Automation, Art & Culture, Cloud Platforms, Command Line, Communication, Customer Data Platforms, etc.) allowing developers to browse servers by use case rather than keyword search. Each category groups related servers, enabling developers to compare multiple solutions within a domain and understand what capabilities the MCP ecosystem provides in that area.
Unique: Pre-organizes MCP servers by functional domain (Browser Automation, Cloud Platforms, Communication, etc.) rather than requiring developers to search by keyword, reducing discovery friction for developers exploring what's possible in a specific area
vs alternatives: Faster domain exploration than GitHub topic search because categories are curated and pre-populated, whereas GitHub requires knowing relevant topics and filtering through unrelated results
Aggregates and displays standardized metadata for each indexed MCP server including creator/author name, GitHub repository URL, last update timestamp, community star count (from GitHub), and server description. The registry pulls this metadata from GitHub and presents it in a consistent format across all 28,999+ server listings, enabling developers to quickly evaluate server provenance, maintenance status, and adoption level.
Unique: Standardizes and displays GitHub metadata (stars, last update, repo URL) for all 28,999+ MCP servers in a consistent format, whereas developers previously had to visit individual GitHub repositories to compare these signals across multiple servers
vs alternatives: Reduces evaluation friction vs visiting 10+ GitHub repositories individually by presenting comparable metadata in a single interface
Displays creator/author information for each MCP server and links to their GitHub profile or repository, enabling developers to identify who maintains a server and access their other work. The registry preserves creator attribution across all indexed servers, supporting community recognition and enabling developers to evaluate creator track record and expertise.
Unique: Preserves and displays creator attribution for all indexed MCP servers, enabling developers to evaluate server quality based on creator track record and find other work by the same author, whereas a generic server list would obscure creator identity
vs alternatives: Enables creator-based discovery and reputation evaluation that GitHub search alone cannot provide without manually visiting each repository
Indexes MCP servers regardless of implementation language or description language, as evidenced by server listings with descriptions in non-English languages. The registry aggregates servers across the entire MCP ecosystem without language-based filtering, enabling global developer discovery while preserving original server descriptions and metadata.
Unique: Indexes MCP servers globally without language-based filtering, preserving original descriptions in multiple languages, whereas language-specific registries would fragment the ecosystem and reduce discoverability for international developers
vs alternatives: Provides unified global MCP discovery vs language-specific registries that would require developers to search multiple sources
Provides direct links to GitHub repositories for each indexed MCP server, enabling developers to access source code, review implementation details, check dependencies, and evaluate code quality. The registry maintains repository URLs as a core metadata field, serving as the primary integration point between discovery and actual server adoption.
Unique: Maintains GitHub repository URLs as a core metadata field for all 28,999+ servers, providing one-click access to source code and implementation details, whereas a registry without repository links would require developers to search GitHub separately
vs alternatives: Reduces friction for code review and evaluation by embedding repository links directly in server listings vs requiring separate GitHub searches
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 MCPRepository.com at 18/100. Supabase also has a free tier, making it more accessible.
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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
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