Rightsize a Monolith API

This use case focuses on extracting focused capabilities from a broad monolith API so consumers get only what they need for each use case. Monolith APIs often expose hundreds of endpoints across unrelated domains, forcing consumers to navigate a massive surface area and receive far more data than any single task requires.

Teams need to select only required operations from the monolith and remap them to narrower, purpose-built resources and tools. Output filtering and mapping publish smaller payloads for each consumer scenario. Passthrough forwarding with target namespace handles routes where full transformation is not needed. Each extracted capability becomes a focused, discoverable unit.

Pain Points

• Monolith APIs expose hundreds of endpoints across unrelated business domains
• Consumers must navigate a massive surface area to find relevant operations
• API responses return far more data than any single task requires
• No way to extract a subset without rewriting the monolith
• AI agents are overwhelmed by the breadth of available tools from a monolith
• Deprecating or evolving monolith endpoints affects all consumers simultaneously

Expected Outcomes

• Focused, purpose-built capabilities extracted from the monolith
• Consumers find exactly the operations they need without navigating the full surface
• Smaller, filtered payloads tailored to each consumer scenario
• No monolith rewrite required—selective extraction only
• AI agents interact with focused tools instead of the full monolith surface

Narrative

An organization runs a large monolith API that has grown over years to cover dozens of business domains—hundreds of endpoints serving web clients, mobile apps, partner integrations, and now AI agents. Every consumer must understand the full surface area to find the handful of operations they actually need.

Teams begin extracting focused capabilities by selecting only required operations from the monolith in capability specs. These operations are remapped to narrower exposed resources and tools with clear, business-oriented naming. Output filtering and mapping publish purpose-built payloads—each consumer scenario gets exactly the data it needs.

Where full transformation is unnecessary, selected routes are forwarded with target namespace as passthrough paths. Not every monolith endpoint needs reshaping—some just need to be discoverable under a clearer name. The approach is incremental: extract what matters first, leave the rest in place.

Each extracted capability becomes a focused, discoverable unit in the catalog. AI agents interact with a handful of relevant tools instead of the full monolith surface. Teams can evolve or deprecate monolith endpoints behind the capability layer without breaking consumer contracts. The monolith stays running—but consumers no longer have to deal with it directly.