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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Executes arbitrary SQL queries against MySQL databases through an MCP server interface that manages persistent connections via connection pooling. The implementation handles query parsing, execution, result serialization, and error propagation back to MCP clients, supporting both read and write operations with configurable timeout and resource limits.
Unique: Implements MySQL access as an MCP tool rather than a direct library, allowing LLM agents to invoke database queries through the MCP protocol with standardized tool schemas, enabling multi-step agentic workflows that interleave database operations with other tools
vs alternatives: Provides database access to LLM agents without requiring custom Python bindings or API wrappers, whereas alternatives like direct mysql-connector-python require agents to manage connection lifecycle and error handling themselves
Discovers and exposes MySQL database schema metadata (tables, columns, indexes, constraints, data types) through MCP tools that query the INFORMATION_SCHEMA system tables. This enables LLM agents to understand the database structure before constructing queries, supporting dynamic schema exploration without hardcoded table definitions.
Unique: Exposes schema introspection as MCP tools that agents can call dynamically, allowing real-time schema discovery integrated into agentic reasoning loops rather than requiring upfront schema documentation or static configuration
vs alternatives: Enables agents to adapt to schema changes without redeployment, whereas static schema definitions in tools like LangChain's SQLDatabase require manual updates when database structure changes
Enforces configurable access controls at the MCP server level, allowing administrators to define which databases, tables, and operations (SELECT, INSERT, UPDATE, DELETE) are permitted for different client identities. Access rules are evaluated before query execution, preventing unauthorized data access through the MCP interface without requiring separate MySQL user accounts.
Unique: Implements access control at the MCP server boundary rather than relying on MySQL user accounts, enabling fine-grained per-client restrictions without creating separate database users for each agent or client identity
vs alternatives: Provides centralized access control for multiple agents sharing a single MySQL connection, whereas alternatives like separate MySQL users require managing N user accounts and connection strings for N agents
Catches SQL execution errors, syntax errors, and connection failures, then returns structured error information to MCP clients including error codes, messages, and context about what failed. Implements basic query validation (e.g., detecting dangerous operations like DROP TABLE) before execution to prevent accidental data loss.
Unique: Implements server-side query validation and error handling at the MCP boundary, preventing malformed or dangerous queries from reaching the database and providing structured error responses that agents can reason about
vs alternatives: Catches errors before database execution and returns structured diagnostics, whereas direct mysql-connector-python usage requires clients to parse raw MySQL error objects and implement their own validation logic
Automatically generates MCP tool schemas that describe available database operations (query execution, schema inspection, etc.) with proper input/output specifications, allowing MCP clients like Claude Desktop to discover and invoke database capabilities through the standard MCP protocol. Schemas include parameter descriptions, type information, and required fields.
Unique: Generates MCP-compliant tool schemas that expose database operations as first-class MCP tools, enabling seamless integration with MCP clients without requiring manual tool registration or schema definition
vs alternatives: Provides automatic tool discovery through MCP protocol, whereas alternatives like LangChain's SQLDatabase require manual tool wrapping and registration in the agent framework
Supports explicit transaction control including BEGIN, COMMIT, and ROLLBACK operations, enabling multi-statement transactions with atomic semantics. Transactions are scoped to a single connection and can be nested using savepoints, with automatic rollback on connection errors or explicit ROLLBACK commands.
Unique: Exposes transaction control as MCP tools, allowing LLM agents to explicitly manage transaction boundaries and implement rollback logic without embedding transaction code in queries
vs alternatives: More explicit than auto-commit mode because agents can reason about transaction scope and implement conditional rollback based on query results, improving reliability of multi-step operations
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 MySQL at 20/100.
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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