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How MoEngage turned over 400 APIs into agent tools with AgentCore Gateway

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How MoEngage turned over 400 APIs into agent tools with AgentCore Gateway

This post was co-written with Nikhil Kumar and Shakir Khan from MoEngage.

When engineering teams start building AI agents, the capabilities those agents need usually already exist as internal APIs. Campaign creation, segment queries, delivery stats. The challenge isn’t building new functionality. The challenge is making hundreds of private APIs safely reachable by agents without exposing them to the public internet, without giving models control over identity, and without flooding context windows with hundreds of tool definitions.

MoEngage, the agentic customer engagement platform that more than 1,350 consumer brands use to deliver personalized experiences across push, email, in-app, SMS, WhatsApp, and RCS, faced exactly this problem. Behind the product sit roughly 400 internal REST APIs, built by 25 engineering teams, running in private virtual private clouds (VPCs) across seven AWS Regions. MoEngage isolates these APIs regionally to meet data residency commitments and doesn’t expose them to the public internet. The capability the agents needed was already running in production. Making it reachable, safely, was the hard part.

In this post, we walk through how MoEngage used AgentCore Gateway, a capability of Amazon Bedrock AgentCore, to turn those private APIs into permission-scoped agent tools. The approach saved MoEngage an estimated six months of platform engineering effort, and onboarding a new API now takes hours instead of days. No product team wrote Model Context Protocol (MCP) server code, no networking was provisioned per integration, and no public endpoint exists anywhere in the path.

The Model Context Protocol (MCP) gives agents a standard way to discover and call tools.


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