| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Provides a centralized registry for defining and managing MCP tools with JSON Schema validation. Tools are registered with name, description, input schema, and handler functions, enabling both the hosted Zerobuild server and stdio transport clients to discover and invoke tools through a unified interface without duplicating tool definitions across multiple transport implementations.
Unique: Centralizes tool definitions for dual-transport MCP architecture (hosted server + stdio), eliminating tool definition duplication and ensuring schema consistency across deployment modes through a single registration point
vs alternatives: Reduces boilerplate compared to defining tools separately for each MCP transport by providing a shared registry that both hosted and local transports consume
Manages MCP resources (documents, files, data sources) with URI-based addressing and content serving. Resources are registered with URI templates, MIME types, and content providers, allowing clients to request resources by URI and receive content with proper type information. Supports both static resources and dynamic content generation through provider functions.
Unique: Provides unified resource registration for both hosted and stdio MCP transports, supporting dynamic content generation through provider functions rather than requiring pre-materialized files
vs alternatives: Simpler than building custom REST endpoints for resource serving because it integrates directly with MCP protocol semantics and works across both hosted and local transport modes
Registers reusable prompt templates with parameter placeholders and metadata, enabling LLM clients to discover and invoke parameterized prompts. Templates support variable substitution, argument validation, and optional descriptions for each parameter. Prompts are registered once and made available across all MCP transport implementations without duplication.
Unique: Centralizes prompt template definitions for dual-transport MCP (hosted + stdio), allowing LLM clients to discover and invoke parameterized prompts without requiring separate prompt management systems
vs alternatives: More integrated than external prompt management tools because prompts are registered alongside tools and resources in a single MCP server, reducing context switching
Provides a unified API for registering tools, resources, and prompts that works transparently across both the hosted Zerobuild server and stdio transport implementations. The same registration calls populate both transport layers, eliminating the need to maintain separate registration logic for each transport mode. Uses dependency injection or factory patterns to adapt registrations to transport-specific requirements.
Unique: Abstracts away transport-layer differences (hosted HTTP vs stdio) through a unified registration API, allowing developers to write transport-agnostic MCP server code that works identically in both deployment modes
vs alternatives: Eliminates transport-specific boilerplate compared to manually implementing separate registration paths for hosted and stdio, reducing code duplication and maintenance burden
Provides TypeScript interfaces and type definitions for tools, resources, and prompts, enabling compile-time type checking of tool schemas, handler function signatures, and parameter types. Tool handlers are typed to match their input schemas, and resource providers are typed to return correct content types. Uses TypeScript generics to enforce type safety across the registration and invocation pipeline.
Unique: Provides full TypeScript support for MCP tool and resource definitions with generic types that enforce schema-handler matching at compile time, preventing runtime type mismatches
vs alternatives: Better developer experience than untyped MCP libraries because TypeScript catches schema-handler mismatches before deployment, reducing debugging time
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 @zerobuild/mcp-core 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