MCP Dev Summit Mumbai 2026

An agent processes a payment, hits a timeout, and retries. Now the payment has been charged twice. The model didn’t hallucinate. The workflow did exactly what it was told. The problem is that nobody designed the agent to be safe under retry.

This is a distributed systems problem.

When agents read data, take actions, and write results back, correctness depends on how state is managed across steps. Under retries or concurrent execution, the same workflow can produce conflicting outcomes.

This talk shows how to build stateful AI agents using the Model Context Protocol with a PostgreSQL-compatible distributed database. Instead of treating memory as embeddings, we treat it as structured, transactional state.

You will learn how to design MCP tools for database operations, manage multi-step workflows, and handle failure modes such as retries and idempotency. We will also explore consistency tradeoffs in distributed systems.

The session ends with concrete patterns for building reliable agents, including idempotent tools and safe retry design.