Supabase ranks higher at 42/100 vs @sit-onyx/modelcontextprotocol at 20/100. Capability-level comparison backed by match graph evidence from real search data.
| Feature | @sit-onyx/modelcontextprotocol | 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 |
Exposes Onyx-specific tools and capabilities through the Model Context Protocol (MCP) server interface, allowing LLM clients to discover and invoke Onyx operations via standardized MCP tool schemas. The server implements the MCP specification for tool registration, enabling clients to query available tools, their parameters, and return types through MCP's introspection mechanism.
Unique: Provides native MCP server bindings specifically for Onyx, eliminating the need for custom MCP wrapper implementations and ensuring compatibility with the Onyx API surface through direct protocol translation.
vs alternatives: Simpler than building a custom MCP server wrapper because it handles Onyx-specific tool schema mapping natively, reducing integration boilerplate for teams already using MCP clients.
Exposes Onyx resources (documents, knowledge bases, configurations, or other Onyx entities) through MCP's resource protocol, allowing LLM clients to discover, list, and retrieve Onyx resources via standardized resource URIs. The server implements MCP resource handlers that map Onyx resource types to MCP resource schemas with content negotiation.
Unique: Bridges Onyx's resource model directly to MCP's resource protocol, enabling LLMs to treat Onyx resources as first-class MCP entities rather than requiring custom API wrappers for each resource type.
vs alternatives: More standardized than custom REST API wrappers because it uses MCP's resource protocol, making Onyx resources interoperable with any MCP-compatible client without client-specific integration code.
Manages the MCP server lifecycle including initialization, connection establishment, message routing, and graceful shutdown. Implements the MCP protocol state machine, handling JSON-RPC message parsing, request/response correlation, and error propagation according to MCP specification. Supports both stdio and network transport modes for client connections.
Unique: Implements MCP protocol state machine with native support for both stdio and network transports, handling the full lifecycle from initialization through graceful shutdown without requiring developers to implement protocol-level message handling.
vs alternatives: Reduces boilerplate compared to building MCP servers from scratch because it abstracts away JSON-RPC message correlation, transport switching, and protocol state management.
Translates MCP tool calls and resource requests into Onyx API calls, handling authentication, request formatting, response parsing, and error mapping. The server maintains Onyx client connections and implements request/response adapters that convert between MCP schemas and Onyx API contracts, including parameter validation and type coercion.
Unique: Implements bidirectional schema translation between MCP and Onyx APIs, handling type coercion, parameter mapping, and error normalization without requiring developers to write adapter code for each Onyx operation.
vs alternatives: Cleaner than manual API client code because it automatically maps MCP schemas to Onyx endpoints, reducing the surface area for integration bugs and making the server maintainable as Onyx APIs evolve.
Defines and validates MCP tool schemas that represent Onyx operations, including parameter types, constraints, descriptions, and return types. The server implements schema validation that ensures incoming MCP tool calls conform to the defined schemas before forwarding to Onyx, catching malformed requests early and providing detailed error messages to clients.
Unique: Provides pre-built tool schema definitions for Onyx operations with built-in validation, eliminating the need for clients to guess parameter requirements and catching schema violations before Onyx API calls are made.
vs alternatives: More robust than unvalidated tool calling because it enforces schema compliance at the MCP layer, preventing malformed requests from reaching Onyx and reducing API error rates.
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 @sit-onyx/modelcontextprotocol 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
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