Supabase ranks higher at 42/100 vs Metabase Integration Server at 25/100. Capability-level comparison backed by match graph evidence from real search data.
| Feature | Metabase Integration Server | Supabase |
|---|---|---|
| Type | Product | MCP Server |
| UnfragileRank | 25/100 | 42/100 |
| Adoption | 0 | 0 |
| Quality | 0 |
| 0 |
| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 4 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
This capability allows users to programmatically access and retrieve dashboards from a Metabase instance using a RESTful API. It leverages the Model Context Protocol (MCP) to facilitate seamless integration with AI assistants, enabling them to pull visualizations and data directly into conversational interfaces. The integration is designed to handle authentication and session management automatically, ensuring secure and efficient access to dashboard data.
Unique: Utilizes the Model Context Protocol to streamline interactions with Metabase, allowing for dynamic dashboard retrieval without manual API handling.
vs alternatives: More efficient than traditional REST API calls due to its built-in session management and context-aware retrieval.
This capability enables users to execute SQL queries directly against their Metabase database through an API interface. It employs a structured query language parser that validates and optimizes queries before execution, ensuring that only valid queries are sent to the Metabase server. The results are then formatted into a user-friendly structure for easy consumption by AI applications.
Unique: Incorporates a query validation layer that ensures only syntactically correct SQL is executed, reducing errors and improving performance.
vs alternatives: Faster and more reliable than generic SQL execution tools due to built-in validation and optimization.
This capability allows users to embed Metabase visualizations directly into their applications or AI interfaces. It uses iframe embedding techniques combined with secure token authentication to ensure that only authorized users can view the visualizations. The integration supports dynamic resizing and customization of visual elements to fit various application layouts.
Unique: Utilizes secure token-based authentication for embedding, ensuring that visualizations are protected while being easily integrated into various applications.
vs alternatives: More secure and customizable than standard iframe embedding solutions due to its token management and dynamic resizing capabilities.
This capability automates the generation of reports based on predefined queries and dashboards in Metabase. It uses a scheduling mechanism that triggers report generation at specified intervals, fetching the latest data and formatting it into a structured report. Users can customize the report format and delivery method, whether via email or direct API access.
Unique: Integrates with Metabase's scheduling features to automate report generation, allowing for flexible customization of report formats and delivery methods.
vs alternatives: More flexible than traditional reporting tools, as it allows for dynamic updates based on real-time data from Metabase.
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 Metabase Integration Server at 25/100.
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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
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