| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 11 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Generates a new Model Context Protocol server project by prompting users for project name and directory, then copies a pre-built TypeScript template (src/ directory) to the target location and generates a customized package.json with appropriate configurations. Uses a self-templating architecture where the CLI's own source code serves as the template, eliminating template drift and ensuring generated projects always match the reference implementation.
Unique: Uses self-templating architecture where the CLI's own src/ directory is copied directly to generated projects, ensuring zero template drift and making the CLI itself a living reference implementation that developers can study and extend
vs alternatives: Eliminates template maintenance burden compared to separate template repositories by using the CLI source as the canonical template, guaranteeing generated projects always reflect the latest best practices
Generates MCP server code that supports both stdio (process-based, command-line) and HTTP/SSE (network-based, Server-Sent Events) transport mechanisms, with conditional initialization logic that selects the transport based on environment or configuration. The template includes pre-wired transport handlers that abstract away protocol-level complexity, allowing developers to focus on implementing tools, resources, and prompts without managing transport details.
Unique: Template includes pre-configured transport abstraction layer that decouples MCP primitive implementations (tools, resources, prompts) from transport details, allowing single codebase to serve both stdio and HTTP/SSE without conditional business logic
vs alternatives: More flexible than single-transport MCP servers because generated projects can switch transports via configuration rather than code changes, enabling development/staging/production deployment with identical server code
Provides a testing setup using a JavaScript testing framework (likely Jest or similar based on typical Node.js projects) with example test patterns for tools, resources, and prompts. The template includes test configuration and example tests demonstrating how to test MCP primitives in isolation from the protocol layer, enabling developers to verify business logic without running the full MCP server.
Unique: Template includes example tests that demonstrate testing patterns specific to MCP primitives (tools, resources, prompts), showing how to test business logic in isolation from protocol concerns
vs alternatives: More focused than generic Node.js testing because example tests show MCP-specific patterns like testing tool handlers and service methods without requiring full MCP server setup
Provides a structured pattern for implementing MCP tools (callable functions) that delegate to a service layer, enabling separation of protocol concerns from business logic. The template includes example tools (hello_world) and corresponding service implementations, with clear extension points for adding new tools via tool registration and service method implementation. Tools are defined with JSON schemas for input validation and are automatically exposed via the MCP protocol.
Unique: Template establishes a three-layer architecture (MCP handler → tool registry → service layer) that makes it trivial to add new tools by implementing a service method and registering it, without touching protocol code
vs alternatives: Cleaner separation of concerns than inline tool implementations because service logic is testable independently of MCP protocol, and services can be reused in non-MCP contexts (REST APIs, CLI commands, etc.)
Implements a resource system that exposes URI-addressable data sources (e.g., example://{id}) through the MCP protocol, with a template pattern for implementing resource handlers that fetch and return data. Resources are registered with URI templates and MIME types, and the template includes example implementations showing how to parse URI parameters and return resource content. Enables AI models to reference and retrieve external data sources as context.
Unique: Template provides URI template parsing and parameter extraction patterns that make it straightforward to implement parameterized resource handlers without manual string parsing
vs alternatives: More structured than ad-hoc API endpoints because resources are URI-addressable and self-describing with MIME types, enabling AI models to understand and reference data sources consistently
Implements a prompts system that exposes pre-defined conversation starters and prompt templates through the MCP protocol, allowing AI models to discover and invoke contextual prompts. The template includes example prompts (greeting) and a registration pattern for adding new prompts with arguments. Prompts can include dynamic content and are designed to guide AI model behavior or provide structured conversation templates.
Unique: Template establishes a prompt registry pattern that makes prompts discoverable and versioned as code, enabling teams to treat prompt engineering as a software engineering discipline with version control and testing
vs alternatives: More maintainable than hardcoded prompts in client applications because prompts are centralized in the MCP server and can be updated without client changes, and AI models can discover available prompts dynamically
Provides a complete build system using TypeScript compiler with separate development (watch mode with source maps) and production (minified, optimized) configurations. The template includes npm scripts for building, watching, and testing, with tsconfig.json pre-configured for MCP server development. Build artifacts are output to a dist/ directory, and the package.json main entry point is configured to use the compiled JavaScript.
Unique: Template includes pre-configured tsconfig.json optimized for MCP server development with strict type checking enabled, ensuring type safety across MCP primitive implementations
vs alternatives: Simpler than bundler-based setups (Webpack, esbuild) because it uses native TypeScript compilation, reducing build complexity and making it easier for developers to understand and modify the build process
Generates a customized package.json for each scaffolded project that includes MCP server metadata (name, version, description), npm binary configuration for CLI entry points, dependency declarations for FastMCP and development tools, and build/test scripts. The generated package.json is tailored to the project name provided during scaffolding and includes all necessary configuration for npm publishing and local development.
Unique: Template generates package.json with MCP-specific metadata and binary configuration that matches the template's own package.json structure, ensuring consistency across all generated projects
vs alternatives: More reliable than manual package.json creation because it's generated from the template's validated configuration, reducing configuration errors and ensuring all generated projects have compatible dependency versions
+3 more capabilities
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 Template MCP Server at 26/100.
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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
+1 more capabilities