| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes Upstash Redis operations (GET, SET, DEL, INCR, LPUSH, HSET, etc.) as MCP tools that Claude and other MCP clients can invoke. Implements the Model Context Protocol server specification to translate tool calls into authenticated HTTP requests to Upstash's serverless Redis API, handling connection pooling, request serialization, and response parsing transparently.
Unique: Purpose-built MCP server specifically for Upstash's REST-based Redis API, eliminating the need for developers to write custom MCP tool definitions for Redis operations. Implements Upstash-specific authentication and endpoint routing rather than generic Redis protocol translation.
vs alternatives: Simpler than building custom MCP tools for Redis or using generic database connectors because it pre-packages Upstash-specific authentication and command mapping, reducing boilerplate by ~70% compared to hand-rolling MCP tool definitions.
Implements the Model Context Protocol server specification, handling stdio-based message transport, JSON-RPC 2.0 request/response routing, and capability advertisement. Manages server lifecycle (initialization, resource discovery, tool registration) and ensures compatibility with MCP clients like Claude Desktop by properly implementing the protocol handshake and error handling.
Unique: Provides a minimal, focused MCP server implementation specifically for Upstash rather than a generic MCP framework, reducing dependency bloat and making the server lightweight (~50KB) for deployment in resource-constrained environments.
vs alternatives: Lighter and faster to deploy than generic MCP frameworks like Anthropic's MCP SDK because it's purpose-built for a single service, trading flexibility for simplicity and startup speed.
Manages Upstash API authentication by reading REST API endpoint and token from environment variables or configuration, constructing properly-signed HTTP requests to Upstash's REST API. Implements bearer token authentication and request header construction without exposing credentials in logs or error messages.
Unique: Implements Upstash-specific REST API authentication (bearer token in Authorization header) rather than generic OAuth or API key patterns, matching Upstash's serverless architecture design.
vs alternatives: Simpler than generic credential management libraries because it's tailored to Upstash's specific authentication scheme, eliminating configuration overhead for this use case.
Maps Redis command names and parameters to Upstash REST API endpoints, validating parameter types and counts before sending requests. Implements command-specific parameter serialization (e.g., converting arrays to Redis protocol format for LPUSH, SADD) and response deserialization to return Redis-native types (strings, numbers, arrays, nil).
Unique: Implements command-specific parameter serialization for Upstash's REST API rather than using generic Redis protocol encoding, ensuring compatibility with Upstash's HTTP-based interface while maintaining Redis semantics.
vs alternatives: More reliable than generic Redis clients for Upstash because it's optimized for the REST API's specific request/response format, avoiding protocol translation overhead and incompatibilities.
Advertises available Redis operations as MCP tools with structured schemas, parameter descriptions, and usage examples. Implements the MCP tools list endpoint to allow clients like Claude Desktop to discover what Redis commands are available, their parameters, and expected outputs without requiring manual configuration.
Unique: Provides pre-built tool schemas for common Redis operations rather than requiring developers to manually define MCP tool schemas, reducing setup friction by ~80% for Upstash-specific use cases.
vs alternatives: Faster to integrate than building custom tool schemas because it includes pre-validated Redis command definitions, eliminating trial-and-error schema debugging.
Catches Redis errors, network failures, and Upstash API errors, normalizing them into consistent MCP error responses with descriptive messages. Implements retry logic for transient failures and ensures that client-side errors (invalid commands) are distinguished from server-side errors (Upstash unavailable).
Unique: Implements Upstash-specific error handling that distinguishes between REST API errors, network failures, and Redis command errors, rather than generic HTTP error handling.
vs alternatives: More reliable than generic HTTP clients because it understands Upstash's specific error responses and can provide context-aware error messages to Claude.
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 @upstash/mcp-server at 26/100. @upstash/mcp-server leads on adoption, 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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