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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Provides structured educational content and runnable code examples demonstrating the Model Context Protocol specification, including server/client architecture patterns, message flow, and integration patterns. Uses npm package distribution to deliver learning materials with executable samples that developers can run locally to understand MCP concepts through hands-on experimentation rather than documentation alone.
Unique: Distributes MCP learning materials as an npm package with executable examples rather than static documentation, enabling developers to install and run working protocol implementations locally for hands-on learning
vs alternatives: More practical than reading MCP specification docs alone because it provides runnable code examples, but less comprehensive than official MCP SDK documentation or production-grade MCP implementations
Supplies boilerplate code and architectural patterns for building MCP servers, including request/response handling, tool registration, resource management, and protocol compliance. Templates demonstrate the standard patterns for implementing the server side of the MCP protocol, reducing setup friction for developers building their first MCP integrations.
Unique: Provides MCP server templates as an npm package that developers can install and reference, rather than requiring manual copying from documentation or GitHub repositories
vs alternatives: Faster onboarding than reading MCP spec and writing servers from scratch, but less feature-complete than production MCP SDKs like the official Anthropic MCP SDK
Demonstrates how to build MCP clients that connect to MCP servers, handle protocol messages, manage tool invocation, and process responses. Includes patterns for connection management, request/response correlation, error handling, and resource discovery through the MCP protocol.
Unique: Provides reference implementations of MCP clients as npm package examples, showing the complete flow from connection through tool invocation to response handling
vs alternatives: More concrete than protocol specification alone, but less feature-rich than production MCP client libraries with built-in connection management and retry logic
Includes examples and validation patterns for MCP protocol messages, demonstrating the JSON schema structure for requests, responses, tool definitions, and resource descriptors. Helps developers understand the exact format required for protocol compliance and provides reference examples they can validate against.
Unique: Provides concrete JSON examples and validation patterns for MCP messages as part of an npm package, making protocol compliance testable and verifiable locally
vs alternatives: More practical than reading JSON schema specifications, but less automated than a full protocol validator or linter
Demonstrates how to define tools and resources in MCP format, including JSON schema specifications for tool inputs, resource metadata, and capability declarations. Shows the patterns for creating tool definitions that are compatible with MCP servers and clients, including input validation schemas and documentation.
Unique: Provides reusable patterns and examples for MCP tool definitions as npm package content, enabling developers to copy and adapt tool schemas for their own implementations
vs alternatives: More practical than raw JSON schema documentation, but less automated than a tool definition generator or IDE plugin
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 learn-mcp at 21/100. learn-mcp leads on ecosystem, while Supabase is stronger on quality.
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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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