Existing APIs return human-readable, variably structured responses optimized for frontend rendering — deeply nested JSON, friendly error messages, inconsistent schemas, and missing machine-critical metadata like explicit rate-limit headers and structured error codes. Agents consuming these APIs waste significant context window capacity on parsing and normalization that adds no task value. There is no emerging standard or adapter layer for agent-optimized API contracts, forcing every agent builder to hand-roll brittle parsers.

Agents waste context tokens and developer time parsing messy, human-oriented API responses; every builder hand-rolls brittle normalization code for each integration.

AI agent developers (solo builders to startups) integrating 3+ external APIs who are burning tokens and debugging flaky parsers weekly.

Agent builders already pay for tools like Langchain, API aggregators, and token usage — a layer that compresses API responses into tight, schema-stable, machine-optimal formats directly reduces their largest variable cost (tokens) and their largest time sink (integration maintenance).

MVP: a proxy service covering the top 50 most agent-consumed APIs (Stripe, GitHub, Slack, etc.) that normalizes responses into a compact, typed, agent-optimized schema with structured error codes and rate-limit metadata — deployed as a gateway URL swap requiring zero agent code changes.

The API management market is $6B+ and growing; the agent-specific integration layer captures a new wedge as millions of agents become the dominant API consumer class within 2-3 years.