| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Implements a stateless message echo service using the Model Context Protocol (MCP) standard, which allows client applications to send text messages to the server and receive duplicated output. The server operates as an MCP-compliant endpoint that parses inbound messages, duplicates them, and returns the result through the MCP transport layer (typically stdio or HTTP). This enables seamless integration with MCP-aware clients like Claude Desktop or custom applications without custom protocol implementation.
Unique: Deployed as a Smithery-hosted MCP server, eliminating the need for developers to manage server infrastructure while providing a standards-compliant MCP endpoint. Uses the Model Context Protocol standard for client communication rather than custom REST or WebSocket protocols, enabling direct integration with MCP-aware tools like Claude Desktop without adapter code.
vs alternatives: Simpler to integrate than building a custom echo service because it uses the standardized MCP protocol that Claude and other tools natively understand, whereas a REST-based echo API would require custom client-side MCP-to-HTTP translation logic.
Provides serverless hosting and deployment of the MCP server through Smithery's managed platform, handling server lifecycle management, session isolation, and scalability without requiring developers to provision infrastructure. The server is deployed as a containerized or serverless function that Smithery routes MCP client connections to, managing connection pooling, request routing, and automatic scaling based on demand. Developers access the server via a stable endpoint URL without managing containers, databases, or load balancers.
Unique: Smithery provides managed MCP server hosting with automatic session isolation and scaling, whereas alternatives like Anthropic's MCP reference implementation require developers to self-host on their own infrastructure. This eliminates the operational burden of managing server uptime, scaling, and connection routing.
vs alternatives: Faster to deploy and share than self-hosted MCP servers because Smithery handles infrastructure provisioning and scaling automatically, whereas self-hosting requires Docker, cloud account setup, and ongoing maintenance.
Exposes the echo service through the Model Context Protocol (MCP) interface, allowing MCP-compatible clients (such as Claude Desktop, custom agents, or automation tools) to discover and invoke the echo capability as a tool or resource. The server implements MCP's tool definition schema, which includes the tool name, description, input schema, and execution handler. Clients parse this schema and can invoke the echo tool with arbitrary text input, receiving the duplicated output as a structured MCP response.
Unique: Implements the MCP tool definition standard, enabling clients like Claude Desktop to automatically discover and invoke the echo capability without custom integration code. Uses MCP's standardized tool schema format (JSON Schema) for input validation and client-side type checking, rather than ad-hoc protocol definitions.
vs alternatives: More discoverable and easier to integrate than a custom echo API because MCP clients natively understand tool schemas and can invoke tools without custom client code, whereas a REST API would require manual endpoint documentation and client-side HTTP handling.
Implements a simple message transformation function that takes any inbound text input and returns it duplicated (typically concatenated or repeated twice). The transformation is stateless — no context is maintained between requests, and each echo operation is independent. The server applies this transformation synchronously and returns the result immediately, making it suitable for testing message routing, transport validation, and basic transformation workflows without side effects or persistence.
Unique: Provides a deterministic, side-effect-free transformation that is ideal for testing because the output is always predictable and reproducible. Unlike more complex transformations, the echo operation has no hidden state, caching, or external dependencies, making it a reliable baseline for validating message transport.
vs alternatives: More reliable for testing than using a real transformation service because the echo operation has zero side effects and is guaranteed to be deterministic, whereas production transformations may depend on external services, caching, or state that introduces variability.
Manages independent MCP sessions for multiple concurrent clients connecting to the echo server through Smithery's hosting platform. Each client connection is isolated, with its own session context and request/response handling, preventing cross-client interference or state leakage. The server handles connection lifecycle management (client connect, disconnect, timeout) and routes requests to the appropriate session handler, enabling multiple users or agents to invoke the echo service simultaneously without blocking or contention.
Unique: Smithery's managed hosting automatically handles session isolation and multi-client routing, whereas self-hosted MCP servers require developers to implement session management, connection pooling, and request routing manually. This eliminates the need for custom session middleware or distributed session stores.
vs alternatives: Simpler to deploy multi-client MCP services because Smithery handles session isolation automatically, whereas self-hosted servers require implementing connection management, session state tracking, and cleanup logic that adds significant complexity.
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 Simple Echo Server at 28/100.
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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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