| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Paid | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Provides a searchable, categorized directory of 2,227+ MCP servers with full-text search, filtering by server name/description, and category-based browsing. The registry indexes server metadata (name, description, category tags, client compatibility) and surfaces results through a web interface with sorting and filtering capabilities. Search operates across server names, descriptions, and tags to help users locate relevant integrations without manual GitHub exploration.
Unique: Centralizes MCP server discovery in a single indexed directory rather than requiring manual GitHub exploration or community forum searches. Implements category-based taxonomy and multi-client compatibility filtering (Cursor, Windsurf, Highlight, Claude, Goose, Cline) to surface relevant servers based on user's specific client environment.
vs alternatives: Faster than GitHub search for MCP discovery because it pre-indexes server metadata and provides client-specific filtering, whereas GitHub requires manual keyword searches across thousands of repositories with no standardized MCP server tagging.
Aggregates and links to setup guides for each MCP server, with instructions tailored to specific MCP clients (Cursor, Windsurf, Highlight, Claude, Goose, Cline). The directory maps each server to client-specific configuration patterns and provides direct links to official setup documentation. This eliminates the need to manually search for client-specific configuration syntax across different server repositories.
Unique: Curates setup guides across multiple MCP clients in a single directory, mapping each server to client-specific configuration patterns. Rather than requiring users to search each server's README for client-specific instructions, MCPServers.com pre-indexes and links to the correct setup path for each client combination.
vs alternatives: Reduces setup friction compared to reading individual server READMEs because it provides client-specific navigation and aggregates setup instructions in one place, whereas users typically must visit each server's GitHub repository and manually search for their client's configuration syntax.
Indexes MCP server metadata (name, description, category tags, supported clients, server type) into a structured registry that enables filtering and browsing by category. The directory maintains a taxonomy of server categories (automation, testing-quality, and others) and associates each server with relevant tags. This structured indexing allows users to browse servers by functional category rather than searching by name.
Unique: Maintains a standardized metadata schema for MCP servers (name, description, category, client compatibility) and indexes this across 2,227+ servers, enabling category-based discovery. This structured approach differs from GitHub's unstructured tagging by enforcing a consistent taxonomy and making category-based filtering reliable.
vs alternatives: More discoverable than GitHub's topic-based filtering because MCPServers.com uses a curated, standardized category taxonomy, whereas GitHub relies on inconsistent topic tags that vary widely across repositories and may not reflect MCP server functionality.
Maps each MCP server to the specific MCP clients it supports (Cursor, Windsurf, Highlight, Claude, Goose, Cline) and enables filtering by client compatibility. The directory maintains a compatibility matrix that indicates which clients can use each server, allowing users to filter the registry to show only servers compatible with their chosen client. This eliminates the need to manually check each server's documentation for client support.
Unique: Maintains a client compatibility matrix across 6 major MCP clients (Cursor, Windsurf, Highlight, Claude, Goose, Cline) and enables filtering by client, centralizing compatibility information that would otherwise be scattered across individual server READMEs. This approach treats client compatibility as a first-class indexing dimension.
vs alternatives: Faster than checking individual server READMEs for client support because MCPServers.com pre-indexes compatibility across all clients and provides one-click filtering, whereas users typically must visit each server's documentation to verify client support.
Displays each MCP server as a structured listing card containing server name, description, category tags, supported clients, and a direct link to the server's official repository or documentation. The listing provides enough metadata to evaluate a server without leaving the directory, while linking to authoritative sources for detailed setup and implementation information. This balances discoverability with directing users to canonical documentation.
Unique: Presents MCP servers as structured listing cards with standardized metadata fields (name, description, category, client support) rather than unstructured GitHub repository links. This consistent presentation format makes it easy to scan and compare servers, whereas GitHub search results are unstructured and require manual inspection of each repository.
vs alternatives: More scannable than GitHub search results because MCPServers.com uses a consistent card-based layout with standardized metadata fields, whereas GitHub displays raw repository listings with variable information density and requires clicking into each repo to understand compatibility and setup requirements.
Maintains a curated directory of 'high-quality' MCP servers (per artifact description) through editorial selection rather than accepting all community submissions. The directory presumably applies quality criteria (documentation completeness, maintenance status, user feedback) to determine which servers are listed, creating a filtered view of the MCP ecosystem that excludes abandoned or poorly-documented servers. This curation reduces noise and helps users find reliable integrations.
Unique: Applies editorial curation to filter the MCP server ecosystem to 'high-quality' servers, reducing noise and helping users avoid abandoned or poorly-documented projects. This differs from GitHub's open indexing by actively gatekeeping which servers appear in the directory based on quality criteria.
vs alternatives: More trustworthy than GitHub search for finding reliable servers because MCPServers.com curates the directory to exclude low-quality projects, whereas GitHub indexes all repositories regardless of maintenance status or documentation quality, requiring users to manually evaluate each server.
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 MCPServers.com at 22/100. MCPServers.com leads on quality, while Supabase is stronger on ecosystem. 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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