MCP Dev Summit Mumbai 2026

**Space Limited - First Come, First Served.  Please bring a fully charged laptop to the workshop**

As agentic systems evolve from single-step tasks to orchestrated workflows, maintaining structured, evolving context becomes a core engineering challenge. While Retrieval-Augmented Generation (RAG) improves access to information, most implementations treat the knowledge source as a static, read-only repository, making it difficult to capture relationships, causality, and decision history across sessions.

This hands-on workshop focuses on operationalising a context engine using MCP—showing how to build a system where agents can read, write, and reason over shared structured context.

Participants will work through a guided implementation to:

* Design a minimal context graph schema for a real-world workflow.
* Ingest and normalise data into a structured representation.
* Expose the context layer via MCP servers.
* Enable agents to query and update context through MCP tools.
* Persist reasoning state across sessions and agent boundaries.

By the end of the session, attendees will have built a working foundation for a context engine and understand how to evolve it into a shared context layer for multi-agent orchestration.

The default AI stack today ships user data to a cloud endpoint and hopes for the best. But regulations like GDPR, India's DPDP Act, and sector-specific mandates (healthcare, finance, defense) increasingly demand that sensitive data never leave the device or jurisdiction. This talk presents a working architecture that squares the circle: run frontier-class SLMs (Phi-3 Mini, Gemma 2B) locally via Meta's ExecuTorch runtime on Android, while using Anthropic's Model Context Protocol (MCP) as the orchestration layer that decides what runs where, which tools the model can access, and what data governance policies are enforced — all without a single byte of PII hitting an external server.