Enable AI assistants to query and optimize PostgreSQL databases using natural language via a secure MCP server deployed on AWS ECS Fargate with credential isolation.
A production-grade Model Context Protocol (MCP) server for PostgreSQL that enables AI assistants to perform natural language SQL generation, schema inspection, query optimization, and database health diagnostics without exposing raw database credentials to client applications. Supports Admin and Tenant operating modes deployed on AWS ECS Fargate.
The Tech 42 PostgresSQL Text-to-SQL MCP Server lets AI assistants query, analyze, and optimize PostgreSQL databases using natural language, no SQL expertise required. Whether you're running AI agents with AWS Bedrock, building agentic workflows, or giving teams a safe database interface, this Model Context Protocol (MCP) server delivers schema discovery, text-to-SQL generation, query optimization, and database health monitoring out of the box.
Built for AWS, the server deploys as a container on Amazon ECS Fargate behind an Application Load Balancer, with credentials managed through AWS Secrets Manager. It connects to Amazon RDS and other PostgreSQL instances via VPC Peering, keeping all database traffic private. Two access modes: Admin for development and DBA workflows, and Tenant Mode for multi-tenant apps with row-level security (RLS); make it flexible for both internal tools and customer-facing applications.
Key capabilities include: natural language SQL, slow query analysis, index recommendations, workload analysis, hypothetical index planning with HypoPG, schema inspection, and comprehensive database health checks. Compatible with Claude, AWS Bedrock Agents, and any MCP-enabled AI agent framework.
Highlights
AI-powered natural language SQL generation converts plain English into optimized PostgreSQL queries, eliminating the need for SQL expertise. Schema discovery, slow query analysis, index recommendations, and hypothetical index planning with HypoPG give teams comprehensive database intelligence through a single MCP interface - compatible with any MCP-enabled AI framework.
Flexible access modes: Unrestricted for dev/DBA workflows, Restricted for read-only production diagnostics, and Tenant Mode for multi-tenant apps with row-level security.
Deploys as a fully managed container on Amazon ECS Fargate behind an Application Load Balancer with no servers to maintain.
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Try this product free for 30 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
This product uses a single usage-based dimension: Container Hours. You pay for each hour the container runs, billed by actual usage. There are no tiers or fixed commitments. Your cost scales directly with how long the server stays active. The longer you run it, the more hours accrue. This server lets AI agents query a PostgreSQL database in plain English and run read-only optimization checks. Because billing is hourly, your total depends on your own runtime rather than a set plan size.
Top-of-mind questions for buyers
What counts as one Container Hour for billing?
A Container Hour measures each hour the MCP server container runs on AWS. The meter tracks running time only. If the container runs for part of an hour, billing follows the partial runtime by that unit. Multiple running containers each accrue their own hours at the same time.
Am I charged when the container is stopped or idle?
Charges apply only while the container runs. A fully stopped container does not accrue Container Hours. Underlying AWS infrastructure, such as storage, may still incur separate AWS fees, but the software meter counts running time alone. Your cost tracks the hours the server stays active.
Does query volume or database size affect my Container Hours?
No. Billing depends on how long the container runs, not on how many queries you send or how large your PostgreSQL database is. Running many plain-English queries in one hour costs the same as running few. Only elapsed runtime drives the Container Hours meter.
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