Supabase ranks higher at 42/100 vs @psraghuveer/memento-server at 23/100. Capability-level comparison backed by match graph evidence from real search data.
| Feature | @psraghuveer/memento-server | Supabase |
|---|---|---|
| Type | MCP Server | MCP Server |
| UnfragileRank | 23/100 | 42/100 |
| Adoption | 0 | 0 |
| Quality | 0 |
| 0 |
| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Translates incoming MCP (Model Context Protocol) tool call requests into command-registry invocations by parsing MCP schemas and mapping them to registered command handlers. Acts as an adapter layer that converts MCP's standardized tool-calling format into Memento's internal command execution model, enabling LLM clients to invoke Memento commands through the MCP interface without direct knowledge of Memento's command architecture.
Unique: Implements a bidirectional adapter pattern that maps MCP's tool-calling semantics directly onto Memento's command-registry architecture, allowing MCP clients to invoke Memento operations without requiring Memento to implement full MCP server capabilities independently
vs alternatives: Lighter-weight than building a full MCP server from scratch because it leverages Memento's existing command registry, reducing boilerplate and maintaining a single source of truth for command definitions
Automatically generates MCP tool definitions from Memento command registry schemas by introspecting registered commands and converting their signatures into MCP-compliant tool schemas. Validates incoming MCP tool calls against these schemas before execution, ensuring type safety and argument correctness. Uses schema-based validation to catch malformed requests early and provide detailed error messages that guide clients toward correct invocation patterns.
Unique: Performs bidirectional schema mapping: introspects Memento command signatures to generate MCP schemas, then validates incoming MCP calls against those schemas, creating a type-safe bridge without requiring manual schema duplication
vs alternatives: Eliminates manual schema maintenance compared to hand-writing MCP tool definitions, because schema definitions are derived from a single source of truth (the command registry)
Persists command execution context and results to a local SQLite database, enabling Memento commands to maintain state across MCP invocations. Stores command history, arguments, and results in structured tables, allowing subsequent commands to query prior execution context without relying on external state stores. Uses SQLite's embedded architecture to provide zero-configuration persistence that works offline and requires no network dependencies.
Unique: Integrates SQLite directly into the MCP server adapter, storing command context in structured tables that are queryable by subsequent commands, rather than using ephemeral in-memory state or requiring external vector databases
vs alternatives: Simpler and faster than RAG-based context retrieval for command history because it uses direct SQL queries on structured command data, avoiding embedding overhead and vector similarity search latency
Maintains execution state across multiple MCP tool calls by storing command results in SQLite and making them available as context for subsequent commands. Implements a context-passing mechanism where each command can query the execution history and use prior results as inputs, enabling multi-step workflows where later commands depend on earlier outputs. Uses SQLite queries to retrieve relevant context without requiring explicit state management from the MCP client.
Unique: Implements implicit context carryover where commands automatically have access to prior execution results via SQLite queries, without requiring the MCP client to explicitly manage or pass state between calls
vs alternatives: More seamless than prompt-based context injection because it uses structured SQL queries on actual command results rather than serializing context into LLM prompts, reducing token overhead and improving precision
Manages the startup, runtime, and shutdown lifecycle of the MCP server adapter, including initialization of the SQLite database, registration of command handlers, and cleanup of resources on shutdown. Implements graceful shutdown that flushes pending command executions to SQLite before terminating, preventing data loss. Provides health check endpoints and status reporting for monitoring server availability and command registry state.
Unique: Implements a complete lifecycle manager that handles both startup initialization (database schema creation, command registry loading) and graceful shutdown (pending command flushing to SQLite) as integrated concerns, rather than leaving these to the caller
vs alternatives: More robust than manual lifecycle management because it automatically handles database initialization and graceful shutdown, reducing boilerplate and preventing data loss from abrupt termination
Catches command execution errors and formats them as MCP-compliant error responses with appropriate error codes, messages, and context. Distinguishes between schema validation errors, command execution errors, and system errors, providing different error codes and recovery suggestions for each category. Logs errors to both the MCP response and internal logs for debugging and monitoring purposes.
Unique: Implements error categorization that maps internal Memento errors to MCP error codes, providing clients with standardized error responses while maintaining detailed internal logs for debugging
vs alternatives: More informative than generic error responses because it categorizes errors by type (validation, execution, system) and provides specific error codes that guide clients toward recovery actions
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 @psraghuveer/memento-server at 23/100. @psraghuveer/memento-server 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
+1 more capabilities