Postgres Pro is an open source Model Context Protocol (MCP) server built to support you and your AI agents throughout the entire development process—from initial coding, through testing and deployment, and to production tuning and maintenance.
MCP server with 14 tools for PostgreSQL database operations. Query databases, explore schemas, analyze tables, with SQL injection prevention and read-only mode by default.
Enables AI agents to interact with PostgreSQL databases through schema intelligence, query execution, and DBA tooling including index analysis and health monitoring. Features configurable access levels and audit logging for secure database operations.
Enables AI agents to execute SQL queries and introspect PostgreSQL schemas, tables, and indexes with read-only safety by default. Supports optional write operations and works with Claude, LangChain, and other agents via stdio or HTTP transports.
what is go-mcp-postgres?
go-mcp-postgres is a Model Context Protocol (MCP) server designed for interacting with Postgres databases, allowing for easy CRUD operations and automation without the need for a Node.js or Python environment.
Enables comprehensive PostgreSQL database management through natural language including queries, schema operations, user management, and administrative tasks. Features enterprise-grade connection pooling, transaction support, and full database administration capabilities.
A server implementing the Model Context Protocol (MCP) for Cursor that allows using a PostgreSQL database as storage for model contexts, enabling secure database exploration and querying.
An open source Model Context Protocol server for PostgreSQL that provides database health analysis, index tuning, query plan exploration, and safe SQL execution for AI agents throughout the development process.
Enables comprehensive PostgreSQL database management including index tuning, query plan analysis, health monitoring, schema-aware SQL generation, and safe SQL execution with configurable access control for both development and production environments.
Enables interaction with PostgreSQL databases through natural language commands. Supports schema exploration, table inspection, DDL generation, data preview, and safe SQL execution with built-in query limits.
Enables AI assistants to safely explore, analyze, and maintain PostgreSQL databases with read-only mode by default, SQL injection prevention, query performance analysis, and optional write operations.
An open-source MCP server that provides AI agents with advanced PostgreSQL capabilities including index tuning, query plan optimization, and comprehensive database health analysis. It supports safe SQL execution through configurable access modes and offers both stdio and SSE transport options for various development environments.
Enables LLMs to query and analyze PostgreSQL databases through a controlled interface. Supports SQL query execution, table schema inspection, and optional write operations with safety controls.
A Model Context Protocol server that enables querying PostgreSQL databases with tools for executing SELECT queries, inspecting database schemas, and listing tables through natural language.
This server enables interaction with PostgreSQL databases through the Model Context Protocol, optimized for the AWS Bedrock AgentCore Runtime. It provides tools for executing read-only queries, exploring database schemas, and monitoring table statistics or slow queries.
A PostgreSQL MCP server that automatically detects and obfuscates personally identifiable information (PII) in query results using column-name heuristics and NLP analysis. It enables AI agents to interact securely with databases by masking sensitive data by default while allowing selective unmasking under user control.
Enables querying and modifying PostgreSQL databases through MCP tools with read/write operations, schema inspection, and write-safety constraints that limit modifications to the mcp schema.
An extended PostgreSQL management and analysis server that provides database professionals with tools for schema management, query optimization, performance monitoring, and health analysis through a collection of specialized functions.