| Ecosystem |
| 1 |
| 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 4 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Implements a pass-through echo mechanism that receives input via MCP protocol, validates formatting and structure, and returns identical output to verify end-to-end connectivity and message integrity. Works by intercepting tool calls through the MCP server interface, parsing the input payload, and echoing it back without transformation, enabling developers to validate that their client-to-server communication pipeline is functioning correctly and that prompts/data structures survive round-trip serialization.
Unique: Minimal, single-purpose MCP server designed explicitly for protocol-level testing rather than functional tool behavior — uses the MCP server interface itself as the validation mechanism, allowing developers to test their MCP infrastructure without external dependencies or side effects.
vs alternatives: Simpler and faster than integration testing against real tools because it eliminates tool logic overhead and external API dependencies, making it ideal for rapid connectivity validation during development.
Registers itself as an MCP tool with a defined schema that declares the echo capability to MCP clients, exposing tool metadata (name, description, input schema) through the MCP protocol's tool discovery mechanism. This allows MCP hosts like Claude Desktop to discover the echo tool, understand its input requirements, and invoke it with properly typed arguments, following the MCP server specification for tool registration and schema validation.
Unique: Exposes a minimal, self-documenting tool schema that serves as a reference implementation for MCP tool registration — the echo tool's simplicity makes it an ideal template for understanding how MCP servers declare and expose tools to clients.
vs alternatives: More transparent than black-box tool implementations because the schema directly reflects the tool's actual behavior, making it useful as a learning tool or reference for MCP integration patterns.
Implements the MCP server transport layer using standard input/output (stdio) as the communication channel, following the MCP specification for JSON-RPC 2.0 message framing over stdio. The server reads JSON-RPC requests from stdin, processes them through the MCP message handler, and writes JSON-RPC responses to stdout, enabling integration with MCP clients that spawn the server as a subprocess and communicate via stdio pipes.
Unique: Uses stdio as the primary transport mechanism, which is the standard for MCP server integration with Claude Desktop — this design choice makes Echo directly compatible with the Claude ecosystem without requiring HTTP or WebSocket infrastructure.
vs alternatives: Simpler deployment than HTTP-based MCP servers because it avoids port management and firewall configuration, making it ideal for local development and Claude Desktop integration.
Enables developers to test prompt templates and data formatting by sending them through the echo tool and inspecting the returned output for serialization errors, encoding issues, or structural problems. The echo mechanism acts as a non-destructive validator that reveals how prompts and structured data are being encoded and transmitted through the MCP protocol without requiring actual tool execution or side effects.
Unique: Provides a zero-side-effect validation mechanism specifically designed for prompt and data formatting by leveraging the echo pattern — developers can iterate on prompts without worrying about tool execution costs or state changes.
vs alternatives: Faster and cheaper than testing against real tools because it eliminates API calls and tool execution, making it ideal for rapid iteration during prompt 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 Echo at 27/100.
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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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