MCP Dev Summit Mumbai 2026

MCP simplifies AI-tool integration — but in high-throughput, latency-sensitive pipelines, its performance characteristics can quietly become the bottleneck. Iterative reasoning loops, sequential tool invocations, and context amplification compound in ways that are easy to miss in development and impossible to ignore in production.

This talk presents a structured decomposition of end-to-end MCP latency — reasoning, communication, execution, and coordination — giving engineers a precise framework for identifying where overhead actually lives. We then present targeted optimizations: parallel tool invocation, streaming responses, schema minimization, and intelligent caching.

The core architectural argument: MCP belongs on the control plane. Separating adaptive orchestration from data-plane execution preserves deterministic performance where it matters, while keeping model-driven flexibility where it adds value. A fast path versus intelligent path pattern follows naturally from this separation. A case study comparing naive and optimized pipeline implementations makes the gains concrete.