| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 11 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Automates Supabase PostgreSQL schema migrations by introspecting the current database state, comparing against desired schema definitions, and generating idempotent SQL migrations. Uses MCP tool protocol to expose migration operations that detect structural changes (tables, columns, constraints, indexes) and generate safe ALTER statements with rollback capability. Bidirectional sync ensures schema definitions stay synchronized with runtime database state without manual intervention.
Unique: Exposes schema migration as MCP tools rather than CLI commands, enabling AI agents and LLMs to autonomously detect schema drift and generate migrations within agentic workflows without subprocess calls or external orchestration
vs alternatives: Unlike Prisma Migrate or Liquibase which require explicit migration files, Supabase Admin infers migrations from schema state comparison, reducing boilerplate while maintaining safety through MCP's structured tool protocol
Introspects Supabase PostgreSQL schema and generates strongly-typed TypeScript interfaces, enums, and utility types that match table structures, relationships, and constraints. Simultaneously scaffolds CRUD operation functions (insert, select, update, delete) with type-safe parameters and return types, leveraging Supabase's PostgREST API. Generated code includes proper null handling, optional fields based on constraints, and relationship types for foreign keys.
Unique: Generates types and CRUD functions as MCP tool outputs that can be invoked by AI agents, enabling autonomous code generation workflows where LLMs can inspect schema and produce application code without manual schema documentation
vs alternatives: More integrated than Supabase's CLI type generation because it operates within MCP protocol, allowing real-time schema inspection and code generation as part of agentic workflows rather than as separate CLI invocations
Aggregates Supabase audit logs (Auth events, API calls, database changes) through MCP tools that provide queryable access to compliance-relevant events. Implements data lineage tracking to understand which users modified which records and when, enabling forensic analysis. Generates compliance reports (SOC 2, HIPAA, GDPR) with configurable retention and export formats for regulatory submissions.
Unique: Exposes audit logging and compliance reporting as MCP tools that enable AI agents to autonomously generate compliance reports and investigate security incidents, with data lineage tracking for forensic analysis
vs alternatives: More integrated than external audit logging services because MCP tools have native access to Supabase's internal audit logs and can track data lineage through RLS policies, while still allowing export to external compliance systems
Manages Supabase PostgreSQL roles, permissions, and RLS policies through MCP tools that abstract the complexity of SQL GRANT statements and policy creation. Enables defining role hierarchies, assigning permissions to tables/functions, and creating RLS policies that enforce row-level data access based on user context (auth.uid(), auth.jwt()). Validates policy logic before deployment and provides policy testing capabilities to verify access control behavior.
Unique: Exposes RLS policy creation and testing as MCP tools that can be invoked by AI agents to autonomously design and validate access control policies based on application requirements, rather than requiring manual SQL policy writing
vs alternatives: More accessible than raw SQL policy management because MCP tools abstract GRANT/REVOKE syntax and provide policy validation, while still maintaining full PostgreSQL RLS expressiveness unlike simplified permission systems
Manages Supabase Auth configuration (providers, settings, JWT secrets) and application secrets through MCP tools that enforce secure storage and rotation patterns. Integrates with Supabase's secret management to store API keys, database credentials, and third-party service tokens without exposing them in code or logs. Supports automated secret rotation schedules and provides audit trails of all secret access and modifications.
Unique: Integrates secret management with MCP protocol, allowing AI agents to autonomously configure Auth providers and rotate secrets based on policies without exposing credentials in agent logs or context windows
vs alternatives: More integrated than managing secrets via Supabase dashboard because MCP tools enable programmatic secret rotation and audit trail queries, while maintaining Supabase's native secret encryption at rest
Exposes Supabase project metrics (database connections, query performance, storage usage, API request rates) through MCP tools that aggregate data from Supabase's monitoring APIs and PostgreSQL system tables. Implements automated health checks that monitor database availability, replication lag, and resource utilization, with configurable alerting thresholds. Provides historical metrics data for trend analysis and capacity planning.
Unique: Aggregates Supabase monitoring APIs and PostgreSQL system tables into MCP tools that can be invoked by AI agents to autonomously detect performance issues and trigger remediation workflows without manual dashboard checks
vs alternatives: More integrated than external monitoring tools (Datadog, New Relic) because it operates within MCP protocol and has native access to Supabase's internal metrics, while still allowing integration with external alerting systems
Manages Supabase Storage buckets through MCP tools that handle bucket creation, configuration, and file lifecycle policies (expiration, archival). Implements access control by creating signed URLs with configurable expiration times and permissions, and manages bucket-level policies for public/private access. Supports automated cleanup of expired files and provides storage usage analytics per bucket.
Unique: Exposes storage bucket management and signed URL generation as MCP tools, enabling AI agents to autonomously manage file access policies and lifecycle without requiring separate S3 SDK calls or dashboard interactions
vs alternatives: More integrated than raw S3 SDK because MCP tools abstract Supabase Storage's specific API and provide lifecycle automation, while maintaining compatibility with S3-compatible storage patterns
Configures Supabase Realtime subscriptions through MCP tools that manage PostgreSQL LISTEN/NOTIFY channels and broadcast subscriptions. Enables defining which tables/events trigger real-time updates, configuring message filtering and transformation, and managing subscription lifecycle. Provides tools to test real-time event delivery and monitor active subscriptions for debugging connection issues.
Unique: Exposes Realtime subscription configuration as MCP tools that can be invoked by AI agents to autonomously set up event streaming based on application requirements, with built-in testing and debugging capabilities
vs alternatives: More accessible than raw PostgreSQL LISTEN/NOTIFY because MCP tools abstract Supabase Realtime's API and provide subscription testing, while maintaining full event filtering and transformation capabilities
+3 more capabilities
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 Admin at 32/100.
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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