Supabase ranks higher at 42/100 vs Moonbeam Smithery MCP Server at 29/100. Capability-level comparison backed by match graph evidence from real search data.
| Feature | Moonbeam Smithery MCP Server | Supabase |
|---|---|---|
| Type | MCP Server | MCP Server |
| UnfragileRank | 29/100 | 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 |
This capability allows applications to securely access decentralized data sources through a standardized protocol, facilitating seamless integration with various blockchain networks. It employs a modular architecture that abstracts the complexities of different blockchain interactions, enabling developers to connect to multiple decentralized data marketplaces without needing to understand the underlying blockchain specifics. The use of a common protocol ensures consistent data retrieval and interaction patterns across diverse platforms.
Unique: Utilizes a modular architecture that abstracts blockchain complexities, allowing for plug-and-play integration with various decentralized marketplaces.
vs alternatives: More flexible than traditional blockchain APIs, as it supports multiple marketplaces through a single integration point.
This capability enables applications to interact with smart contracts deployed on various blockchain networks, allowing for seamless execution of contract functions. It leverages a unified interface that standardizes smart contract calls, reducing the need for developers to write custom code for each blockchain. The server handles the intricacies of transaction signing and gas fee management, streamlining the process of executing smart contract functions.
Unique: Offers a unified interface for smart contract interactions, abstracting the complexities of transaction management and gas fees.
vs alternatives: Simplifies smart contract interactions compared to direct blockchain SDKs, which often require extensive boilerplate code.
This capability allows applications to receive real-time updates from decentralized data sources, utilizing WebSocket connections to push data changes as they occur. The server maintains persistent connections to various blockchain nodes, subscribing to relevant events and broadcasting updates to connected clients. This architecture ensures that applications can react to changes in data without polling, providing a more efficient and responsive user experience.
Unique: Utilizes persistent WebSocket connections to provide real-time data updates, reducing latency compared to traditional polling methods.
vs alternatives: More efficient than REST-based polling solutions, which can lead to increased latency and resource consumption.
This capability orchestrates API calls across multiple decentralized data providers, allowing applications to aggregate data from various sources seamlessly. It employs a centralized management layer that handles the routing of requests and responses, ensuring that developers can access diverse data without managing individual connections. The orchestration layer can also implement caching strategies to enhance performance and reduce redundant API calls.
Unique: Centralizes API management for multiple decentralized providers, simplifying the integration process and enhancing data aggregation capabilities.
vs alternatives: More streamlined than managing individual API integrations, which can lead to increased complexity and maintenance overhead.
This capability provides a secure authentication mechanism for users interacting with decentralized data and smart contracts, utilizing OAuth and JWT tokens to manage user sessions. The server implements a robust authentication flow that ensures secure access to sensitive blockchain functionalities while maintaining user privacy. By leveraging industry-standard authentication protocols, it simplifies the integration of secure access into decentralized applications.
Unique: Implements OAuth and JWT for secure user authentication, ensuring privacy and security in blockchain interactions.
vs alternatives: More secure than traditional session management methods, which may not adequately protect user data in decentralized environments.
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 Moonbeam Smithery MCP Server at 29/100.
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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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