Supabase ranks higher at 42/100 vs @supabase/mcp-server-postgrest at 20/100. Capability-level comparison backed by match graph evidence from real search data.
| Feature | @supabase/mcp-server-postgrest | Supabase |
|---|---|---|
| Type | MCP Server | MCP Server |
| UnfragileRank | 20/100 | 42/100 |
| Adoption | 0 | 0 |
| Quality |
| 0 |
| 0 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Automatically discovers PostgREST-exposed database tables, views, and functions by querying the OpenAPI schema endpoint, then registers them as MCP tools with typed parameters derived from the schema. Uses the MCP tool registry pattern to expose database operations as callable functions with JSON Schema validation, enabling LLM agents to understand available database operations without manual configuration.
Unique: Implements dynamic schema-to-MCP-tool mapping by parsing PostgREST OpenAPI schemas, eliminating manual tool definition — the server introspects the database API surface and auto-generates typed MCP tools with parameter validation derived directly from the REST schema
vs alternatives: Tighter integration with PostgREST than generic REST-to-MCP adapters because it understands PostgREST-specific conventions (RPC endpoints, table naming, auth headers) and automatically maps them to safe, typed tool calls
Translates MCP tool invocations into HTTP requests to PostgREST endpoints, handling parameter binding, query string construction, and response parsing. Supports filtering, sorting, pagination, and RPC function calls by mapping tool arguments to PostgREST query parameters and request bodies, with automatic JSON response deserialization and error handling.
Unique: Implements a parameter-to-PostgREST-query-syntax compiler that translates typed MCP tool arguments into correct HTTP query strings and request bodies, handling PostgREST-specific operators (eq, gt, in, etc.) and response formats without requiring the LLM to understand REST conventions
vs alternatives: More ergonomic than raw REST clients because it abstracts PostgREST's query syntax into typed function parameters, and more flexible than SQL-only approaches because it supports both queries and mutations through a unified tool interface
Manages PostgREST authentication by injecting API keys or JWT tokens into HTTP request headers for each tool invocation. Supports both Supabase API key authentication and custom JWT tokens, with configurable header names and token refresh logic to maintain valid credentials across multiple database operations.
Unique: Implements a credential injection layer that sits between the MCP tool interface and PostgREST HTTP calls, allowing the server to act as a trusted intermediary that holds credentials and enforces authentication without exposing keys to the LLM client
vs alternatives: Safer than passing credentials to the LLM client because authentication is handled server-side, and more flexible than hardcoded credentials because it supports both API keys and JWT tokens with configurable header injection
Implements the MCP server protocol by managing tool registration, request routing, and response serialization. Handles MCP message parsing, tool discovery requests, tool call invocations, and error responses according to the MCP specification, with proper async/await patterns for non-blocking database operations.
Unique: Implements the full MCP server protocol stack for PostgREST, handling tool discovery, invocation routing, and response serialization as a thin adapter layer that translates MCP calls to PostgREST HTTP requests
vs alternatives: Purpose-built for PostgREST integration rather than a generic MCP framework, making it simpler to deploy but less flexible for non-PostgREST use cases
Catches PostgREST HTTP errors (4xx, 5xx responses) and normalizes them into MCP-compatible error responses with descriptive messages. Handles common database errors (constraint violations, authentication failures, not found) and translates them into human-readable error messages that LLM clients can understand and act upon.
Unique: Translates PostgREST HTTP error responses into MCP-compatible error formats with contextual messages, allowing LLM clients to understand database failures without parsing raw HTTP status codes
vs alternatives: More user-friendly than raw HTTP errors because it provides semantic error messages that LLMs can understand and act upon, improving agent reliability
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 @supabase/mcp-server-postgrest at 20/100.
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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