Large Language Models and autonomous agent systems are only as capable as the backend APIs backing them. However, exposing enterprise backend systems to non-deterministic agent callers breaks traditional assumptions around rate limiting, connection pooling, and payload validation.

This talk breaks down how backend engineers can build and scale production-grade MCP (Model Context Protocol) servers and agent-facing interfaces on top of existing services:

From REST/gRPC to Tool Interfaces: Structuring self-describing schemas, dynamic parameter sanitization, and strict input boundaries to eliminate prompt injection via payload parameters.

Taming Non-Deterministic Traffic: How agentic retry loops and multi-step reasoning chains alter backend traffic profiles—and why standard API rate limiters fail against agent workloads.

Stateful Sessions over Stateless Backends: Managing persistent context, Server-Sent Events (SSE), and connection lifecycle without draining socket pools.

Telemetry & Cost Tracking: Tracing request lineages across LLM tool invocations down to backend database queries to catch latency regressions and token bleed.

3 Key Takeaways for Attendees:

Step-by-step guidance on designing lightweight, backward-compatible MCP layers atop enterprise REST and microservice architectures.

Defensive security patterns: sandboxing tool execution, scoped authorization tokens, and payload validation.

Observability patterns for profiling p99 latency regressions when tools are executed inside complex agent reasoning loops.