Supabase ranks higher at 42/100 vs @mseep/mcp-typescript-server-starter at 20/100. Capability-level comparison backed by match graph evidence from real search data.
| Feature | @mseep/mcp-typescript-server-starter | Supabase |
|---|---|---|
| Type | Template | 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 |
Provides a pre-configured TypeScript project template that implements the ModelContextProtocol server specification, including build configuration, dependency management, and server initialization patterns. Uses npm/TypeScript toolchain with pre-wired tsconfig and build scripts to eliminate manual setup of MCP server infrastructure, allowing developers to focus on tool implementation rather than protocol compliance.
Unique: Provides an opinionated MCP server starter specifically for TypeScript with pre-configured build pipeline and protocol bindings, reducing setup friction compared to building from the raw MCP specification
vs alternatives: Faster than implementing MCP servers from scratch using raw protocol documentation because it includes working build configuration and TypeScript type definitions for the MCP spec
Includes TypeScript type definitions that map to the ModelContextProtocol specification, enabling compile-time validation of server requests, responses, and tool definitions. The starter bundles MCP protocol types that enforce correct message structure, tool schemas, and resource definitions, preventing runtime protocol violations through static type checking.
Unique: Bundles MCP protocol types directly in the starter template rather than requiring separate type package installation, reducing dependency management overhead and ensuring version alignment
vs alternatives: More integrated than installing MCP types separately because the starter guarantees type definitions match the bundled MCP implementation version
Provides a pre-configured server entry point that handles MCP protocol initialization, connection lifecycle (startup, shutdown, error handling), and message routing. The starter includes patterns for setting up stdio-based or HTTP-based transport, managing server state, and gracefully handling client connections and disconnections according to MCP specification requirements.
Unique: Provides a complete server initialization pattern that handles MCP protocol handshake and message routing out-of-the-box, eliminating the need to manually implement protocol state management
vs alternatives: Reduces boilerplate compared to implementing MCP server initialization from the protocol specification because it includes working examples of connection handling and message dispatch
Provides a structured pattern for defining tools (with input schemas, descriptions, and execution logic) and registering them with the MCP server. The framework uses a registry-based approach where tools are declared with JSON schemas for input validation and bound to handler functions, enabling the server to automatically expose tools to MCP clients with proper schema documentation.
Unique: Provides a declarative tool registration pattern that separates tool metadata from implementation, enabling automatic schema exposure and client discovery without manual protocol handling
vs alternatives: More maintainable than manually implementing tool exposure because tool definitions and handlers are co-located and schemas are enforced through the registration framework
Includes pre-configured npm scripts, TypeScript build configuration (tsconfig.json), and development tooling setup for building, testing, and running MCP servers. The starter provides scripts for compilation, development mode with hot-reload support, and production builds, eliminating manual configuration of the TypeScript build pipeline and development environment.
Unique: Provides a complete, pre-configured build pipeline specifically optimized for MCP servers, including development mode and production build scripts, eliminating the need to manually configure TypeScript compilation
vs alternatives: Faster to get started than configuring TypeScript and npm scripts from scratch because the starter includes working build configuration tuned for MCP server development
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 @mseep/mcp-typescript-server-starter at 20/100. @mseep/mcp-typescript-server-starter 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
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