Supabase ranks higher at 42/100 vs @alcyone-labs/modelcontextprotocol-sdk at 21/100. Capability-level comparison backed by match graph evidence from real search data.
| Feature | @alcyone-labs/modelcontextprotocol-sdk | Supabase |
|---|---|---|
| Type | Framework | MCP Server |
| UnfragileRank | 21/100 | 42/100 |
| Adoption | 0 | 0 |
| Quality |
| 0 |
| 0 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 7 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Provides runtime schema validation for Model Context Protocol messages using Zod V4's parsing and validation engine. Validates incoming MCP requests, responses, and tool definitions against TypeScript-first schemas, catching type mismatches at runtime before they propagate to LLM integrations. Uses Zod's discriminated unions and refinements to enforce protocol compliance across request/response pairs.
Unique: Upgrades the official MCP SDK to Zod V4, leveraging Zod's improved discriminated union handling and refinement API to provide tighter schema validation for protocol messages than the previous Zod V3 implementation
vs alternatives: Offers better type inference and smaller bundle size than hand-rolled JSON Schema validators, while maintaining full MCP protocol compliance with zero runtime overhead for type checking
Provides TypeScript class-based abstractions for implementing MCP server handlers (tools, resources, prompts) with automatic request routing and response serialization. Handlers are decorated with Zod schemas that define input/output contracts, and the framework routes incoming MCP calls to the correct handler based on method names and validates payloads before execution.
Unique: Combines Zod V4 schema definitions with class-based handler registration to create a declarative, type-safe server framework where input validation and routing are co-located with handler definitions, reducing the gap between schema and implementation
vs alternatives: More ergonomic than raw MCP protocol implementations because it eliminates manual message parsing and routing, while maintaining full protocol compliance and providing better IDE autocomplete than string-based method names
Handles bidirectional conversion between TypeScript objects and MCP protocol JSON messages using Zod schemas as the source of truth. Automatically serializes handler responses into MCP-compliant JSON-RPC format and deserializes incoming requests into typed TypeScript objects, with built-in error handling for malformed messages.
Unique: Uses Zod V4's parse and stringify capabilities to create a bidirectional serialization layer where the schema definition automatically generates both validation and serialization logic, eliminating separate serializer implementations
vs alternatives: More maintainable than manual JSON.stringify/parse with separate validation because schema changes automatically propagate to both serialization and validation, reducing the risk of protocol drift
Enables developers to define MCP tools with Zod schemas that automatically generate capability advertisements sent to LLM clients. The framework introspects Zod schemas to extract parameter descriptions, types, and constraints, then formats them into MCP tool definitions that Claude and other clients use to understand what tools are available and how to call them.
Unique: Leverages Zod V4's metadata system to extract parameter descriptions and constraints directly from schema definitions, eliminating the need for separate tool definition files or manual capability advertisement code
vs alternatives: Reduces tool definition maintenance burden compared to frameworks that require separate schema and tool definition files, because the source of truth is a single Zod schema that drives both validation and capability advertisement
Provides a TypeScript client library for consuming MCP servers with full type inference based on server-advertised tool schemas. The client automatically generates TypeScript types for available tools and their parameters, enabling IDE autocomplete and compile-time type checking when calling remote tools, while handling the underlying JSON-RPC protocol transparently.
Unique: Generates TypeScript types dynamically from server-advertised Zod schemas at runtime, enabling full IDE support and type checking without requiring separate type definition files or code generation steps
vs alternatives: Provides better developer experience than untyped MCP clients because type inference is automatic and stays in sync with server capabilities, while maintaining zero-dependency type safety compared to frameworks requiring separate type generation
Extends the handler framework to support MCP resources (files, documents, knowledge bases) and prompts (reusable instruction templates) with Zod-validated schemas. Developers define resource and prompt handlers using the same class-based pattern as tools, with automatic schema validation and MCP protocol compliance for resource listing, retrieval, and prompt instantiation.
Unique: Applies the same Zod-based handler pattern used for tools to resources and prompts, creating a unified framework where all MCP capabilities (tools, resources, prompts) share consistent validation, routing, and type safety
vs alternatives: More consistent and maintainable than separate resource and prompt implementations because they use the same handler registration and validation patterns, reducing cognitive load and code duplication
Provides structured error handling that converts TypeScript exceptions into MCP-compliant JSON-RPC error responses with proper error codes, messages, and optional error data. Includes built-in error types for common MCP failures (invalid request, method not found, invalid params) and allows custom error handlers to transform application exceptions into protocol-compliant responses.
Unique: Integrates error handling directly into the handler framework so exceptions thrown in handlers are automatically converted to MCP-compliant responses without requiring manual error wrapping in each handler
vs alternatives: Simpler than manual error handling because the framework automatically maps TypeScript exceptions to JSON-RPC error codes, reducing boilerplate and ensuring consistent error formatting across all handlers
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 @alcyone-labs/modelcontextprotocol-sdk at 21/100. @alcyone-labs/modelcontextprotocol-sdk 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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