Building Real-Time, Data-Aware Intelligence with Postgres & Model Context Protocol (MCP)
Presented by:
Yogesh Jain
Yogesh Jain is a Staff SDE at EnterpriseDB and a passionately curious full-stack developer. He specializes in building scalable solutions leveraging open-source technologies, with expertise spanning Kubernetes, observability, distributed systems, and cloud-native PostgreSQL.
He is currently working on developing EDB Postgres AI - a hybrid manager crafted to automate, manage, and observe AI-ready enterprise data across multiple platforms. He is dedicated to solving complex, real-world challenges through pragmatic and scalable engineering. More about him can be found on his personal blog site: curiousone.in/about
No video of the event yet, sorry!
Imagine asking an AI agent to analyze any data, only for it to hallucinate a schema that doesn't exist. This "context gap" is the primary barrier to reliable Data-Aware AI. While LLMs are brilliant reasoners, they are historically "blind" to the live, structured world of Postgres - until now!
In this talk, we will explore how the Model Context Protocol (MCP) bridges this gap, transforming Postgres from a passive storage layer into an active reasoning engine. We’ll dive into the architecture of a Postgres MCP server, demonstrating how it provides agents with secure, structured access to schemas and metadata. By utilizing tools like pg_catalog and EXPLAIN, we enable LLMs to understand table relationships and optimize performance before running queries.
Expect live demos and practical insights.
Key Takeaways:
- How Postgres + MCP provides LLMs with correct, real-time database context.
- Leveraging Postgres metadata and schema to eliminate SQL hallucinations.
- Implementing secure, multi-tenant, and read-only access for AI agents.
- Enabling AI agents to use EXPLAIN and other tools for self-optimization.
- Live demo to deploy a MCP server to connect Postgres with AI agents.
- Date:
- 2026 April 21 09:00 PDT
- Duration:
- 50 min
- Room:
- San Pedro (Level C)
- Conference:
- Postgres Conference: 2026
- Language:
- Track:
- Dev
- Difficulty:
- Easy