| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
This capability allows the MCP server to define and invoke functions based on a schema that supports multiple backend providers. It utilizes a registry pattern to manage function definitions and dynamically routes calls to the appropriate provider based on the request context. This design choice enables seamless integration with various APIs and enhances flexibility in function execution across different environments.
Unique: The use of a schema-based registry allows for dynamic function resolution and provider switching at runtime, which is not common in traditional MCP implementations.
vs alternatives: More flexible than standard MCP servers that typically support only a single provider or require hardcoded integrations.
This capability manages the execution context for functions, allowing the server to maintain state across multiple function calls. It employs a context stack pattern to preserve relevant data between calls, ensuring that each function can access necessary context without requiring external state management. This approach simplifies the development of complex workflows that depend on shared state.
Unique: The context stack pattern allows for efficient state management without external dependencies, which is often a challenge in similar tools.
vs alternatives: More efficient than other MCP servers that require external databases for state management, reducing latency.
This capability enables the MCP server to dynamically route incoming API requests to the appropriate internal or external endpoints based on predefined rules. It uses a routing table that can be modified at runtime, allowing developers to change routing logic without redeploying the server. This flexibility is crucial for applications that need to adapt to changing requirements quickly.
Unique: The ability to modify the routing table at runtime sets this MCP server apart from others that require static configurations.
vs alternatives: More adaptable than traditional API gateways that require redeployment for routing changes.
This capability provides real-time logging of API requests and responses, along with monitoring of server performance metrics. It employs a logging middleware that captures relevant data and streams it to a monitoring dashboard, allowing developers to visualize usage patterns and identify bottlenecks. This proactive approach to monitoring enhances the reliability and maintainability of the server.
Unique: The integration of real-time logging with a monitoring dashboard provides immediate insights, which is often lacking in standard MCP implementations.
vs alternatives: More comprehensive than basic logging solutions that do not offer real-time monitoring capabilities.
This capability allows the MCP server to handle multiple response formats based on client requests, including JSON, XML, and plain text. It utilizes a content negotiation mechanism that inspects request headers to determine the desired format and transforms the response accordingly. This flexibility ensures compatibility with a wide range of clients and enhances the usability of the API.
Unique: The content negotiation mechanism allows for seamless adaptation to client needs, which is not commonly found in simpler MCP servers.
vs alternatives: More versatile than traditional APIs that typically support a single response format.
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 my_new_mcp_server at 24/100. my_new_mcp_server 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
+1 more capabilities