MCP Dev Summit Mumbai 2026

MCP is the protocol layer for the new consumer of software. But protocols are necessary, not sufficient. The next generation of agents won't be soley defined by the protocol they speak — but also the infrastructure that powers it.

In this keynote, Sam Partee (CTO and Co-Founder of Arcade.dev) walks through the agent runtime components needed to drive more adoption of MCP: delegated identity that scopes what an agent can do; tool routing that survives ten thousand registered tools; memory and provenance that turns one-shot demos into auditable systems. Each layer is grounded in production data — what breaks, mistakes we made, what to build, why, and what the next two years of infrastructure work look like.

MCP reached infrastructure currency in 13 weeks. CNCF took 13 months. That compression is the problem. The shared plumbing every production MCP deployment now reinvents, because no neutral open implementation exists yet, has to be built in months instead of years.

This talk maps five missing layers of the MCP ecosystem and what each needs before the protocol scales two more orders of magnitude.

1. Discovery federation. One registry lookup does not survive public, private, and vendor registries coexisting.
2. Workload identity for servers. Not user OAuth. Who is this server, who signed it, what is it allowed to do?
3. Observability backbone. OpenTelemetry semantic conventions for MCP are still draft, so every gateway ships its own trace format.
4. Health and reputation signals. When seventeen servers are named github-mcp, which one should an agent trust?
5. Metering and cost attribution. Boring, load bearing, absent from the spec.

For each layer: what exists today, where it breaks at scale, what a minimum viable open implementation needs. Attendees leave with a concrete map of which gaps are urgent, which are deferrable, and which are already being filled.

The Model Context Protocol (MCP) has fundamentally revolutionized developer velocity, allowing engineers to build and iterate complex AI agents seamlessly on a local machine. However, when moving these autonomous agents from a local sandbox into a production enterprise environment, organizations hit a sudden architectural ceiling. The local agility that fuels early-stage innovation quickly breaks under the compounding pressure of agentic sprawl, fragmented data integrations, and critical compliance requirements.

This keynote addresses the hidden architectural dimensions required to run enterprise AI agents safely and reliably at scale. Moving past individual agent scripts, we will explore why a centralized, fully managed platform is no longer a luxury, but a core system dependency. We will dive into the four essential pillars—Build, Scale, Govern, and Optimize—with a specific focus on how a managed MCP control plane provides the cryptographically-attested identity, granular gateway policies, and runtime isolation required to cross the chasm from an impressive local prototype to a secure, enterprise-grade AI ecosystem.