Supabase ranks higher at 42/100 vs @modelcontextprotocol/server-basic-preact at 21/100. Capability-level comparison backed by match graph evidence from real search data.
| Feature | @modelcontextprotocol/server-basic-preact | Supabase |
|---|---|---|
| Type | MCP Server | MCP Server |
| UnfragileRank | 21/100 | 42/100 |
| Adoption | 0 | 0 |
| Quality | 0 | 0 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 8 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Bootstraps a Model Context Protocol server instance that binds Preact as the rendering framework for server-side UI components. Uses MCP's server initialization pattern to establish bidirectional communication channels between LLM clients and the Preact component tree, enabling declarative UI composition for tool interfaces. The server registers Preact components as MCP resources that can be dynamically rendered and updated based on client requests.
Unique: Uses Preact (not React) as the rendering layer for MCP server UIs, reducing bundle size and runtime overhead compared to full React implementations while maintaining component-based architecture patterns
vs alternatives: Lighter-weight than React-based MCP servers (Preact is ~3KB vs React's ~40KB) while providing the same declarative component model for defining tool interfaces
Allows developers to define MCP tools as Preact components with props mapping to tool parameters and component output mapping to tool results. The server introspects component signatures to auto-generate MCP tool schemas, eliminating manual schema duplication. Tool invocation triggers component rendering with parameters as props, and the rendered output is serialized back as the MCP tool result.
Unique: Derives MCP tool schemas from Preact component prop signatures rather than requiring explicit JSON schema definitions, reducing boilerplate and keeping tool definition and UI in one place
vs alternatives: Eliminates schema duplication compared to traditional MCP servers where tools are defined as functions with separate JSON schemas; component-based approach mirrors modern web development patterns
Exposes Preact components as MCP resources that clients can request and receive as rendered output. The server maintains a registry of component-based resources, handles client resource requests by rendering the corresponding component with optional query parameters, and returns the rendered output (HTML, text, or structured data) as the resource content. Supports dynamic resource generation based on client context.
Unique: Treats Preact components as first-class MCP resources, allowing component rendering logic to be invoked on-demand by MCP clients rather than pre-generating static resource content
vs alternatives: More flexible than static resource files because resource content is generated dynamically at request time; more maintainable than embedding rendering logic in server handlers because components are reusable and testable
Implements MCP's message protocol (requests, responses, notifications) with hooks into Preact component lifecycle. Server receives MCP requests, routes them to appropriate component handlers, executes component render cycles, and sends responses back to clients. Supports both synchronous component rendering and async operations (API calls, database queries) within component lifecycle hooks, with proper error handling and timeout management.
Unique: Integrates MCP's request-response protocol directly with Preact's component lifecycle hooks, allowing async operations to be expressed naturally within component code rather than in separate handler functions
vs alternatives: More idiomatic for Preact developers than traditional MCP servers where request handling is separate from component rendering; reduces context-switching between handler functions and component code
Provides TypeScript-first tool parameter binding by leveraging Preact component prop types to define and validate tool parameters. The server uses TypeScript's type system to auto-generate parameter schemas, validate incoming tool calls against those types, and provide IDE autocomplete for tool parameters. Type mismatches are caught at development time and runtime, with clear error messages for parameter validation failures.
Unique: Uses Preact component prop types as the single source of truth for tool parameters, eliminating the need to maintain separate TypeScript types and JSON schemas
vs alternatives: Provides better IDE support and compile-time safety than JSON schema-based parameter definitions; reduces boilerplate compared to tools that require both TypeScript interfaces and separate schema definitions
Enables state management within MCP server tools using Preact hooks (useState, useReducer, useContext). State is scoped to individual tool invocations or shared across multiple tools via context providers. The server manages hook state lifecycle, ensuring proper cleanup between tool calls and supporting stateful tool interactions across multiple client requests. Integrates with MCP's request-response model to persist state across related tool calls.
Unique: Applies Preact's hooks model (useState, useReducer, useContext) to server-side tool state management, allowing developers to use familiar client-side patterns for server-side state
vs alternatives: More intuitive for Preact developers than traditional MCP servers with manual state management; reduces boilerplate compared to implementing custom state management from scratch
Supports composing multiple Preact components into tool chains where the output of one tool (component) becomes the input to the next. The server manages data flow between composed components, handles error propagation through the chain, and provides a unified interface for executing multi-step tool sequences. Component composition follows Preact's component nesting patterns, making tool chains declarative and reusable.
Unique: Leverages Preact's component composition model to create tool chains, allowing developers to compose tools using familiar component nesting syntax rather than explicit pipeline configuration
vs alternatives: More declarative and reusable than imperative tool chaining; aligns with Preact developers' existing mental models for component composition
Manages separate execution contexts and sessions for multiple concurrent MCP clients connecting to the same server. Each client gets an isolated context with its own state, resource namespace, and tool invocation history. The server routes requests to the correct client context, maintains session metadata (client ID, connection time, request count), and handles client disconnection with proper cleanup. Supports session persistence for reconnecting clients.
Unique: Provides built-in multi-client context isolation at the MCP server level, allowing each client to have separate state and resource namespaces without explicit application-level isolation logic
vs alternatives: Simpler than implementing per-client isolation manually; prevents state leakage between clients without requiring developers to add isolation checks in every tool
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 @modelcontextprotocol/server-basic-preact at 21/100.
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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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