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Your API has a new consumer
Your OpenAPI was designed for humans. Is it ready for AI?
AI agents don't ask when your OpenAPI is ambiguous — they guess. The guess compiles, ships, and fails silently. You don't get a support ticket. You get a silent churn.
Why your audience changed
For a decade, your API had one consumer.
A developer, with your documentation open in another tab. That assumption is now wrong. Three new classes of consumer read your API — and most of the integration traffic is shifting to them. They each read it differently, and none of them route around a gap the way a person does.
A developer routes around an ambiguous API. A machine integrates it — and ships it.
What it costs you
The gap is already visible to your customers.
You won't see it as a bug report. AI failures against your API are quiet — which is exactly what makes them expensive.
Adoption you never see leave
When an agent misuses your API, the developer doesn't file a ticket. They get frustrated, abandon the integration, or ship code that fails later. You see the churn, never the cause.
Tickets from code you didn't write
A growing share of integration support traces back to AI-generated code that hallucinated your API. Your team debugs problems a clearer OpenAPI would have prevented.
"Are you agent-ready?"
Enterprise buyers are starting to ask before they sign. An unscored API reads as risk. A score with a fix plan reads as maturity — and shortens the cycle.
The payoff
When an API is AI-ready, the numbers move.
In controlled runs inside Claude and Cursor, the same integration task against an AI-ready OpenAPI finished faster, cost less, and stopped fabricating calls. The audit tells you how far you are from that — and what it takes to close the gap.
What you get
Not a linter. A measured verdict with a fix plan.
Four pillars, each scored 0–100, rolled into one composite score leadership can act on — backed by evidence your engineers can execute line by line.
Standards & Specification Compliance
Is your OpenAPI valid, structurally correct, and clean enough to generate reliable SDKs, accurate docs, and fast partner onboarding?
General AI Readiness
Can a model understand what your API does from the OpenAPI alone — naming, schemas, responses, anti-patterns — without guessing or inferring?
MCP Server Readiness
Exposed to agents as callable tools over MCP, do they actually execute end-to-end — clean tool schemas, correct auth routing, no destructive surprises?
AI Coding Assistant Readiness
Do Claude, Cursor, and Copilot write correct integration code against your API? Tested with live runs, not just static structure.
A single critical finding caps the composite. It can't be averaged away by clean pillars.
Industry benchmarks
We've scored the APIs your developers compare you to.
Same engine, same rules, same scoring — run against the public OpenAPI definitions of the APIs in your market. Here's the range, and the one question that matters.
Where audited APIs land
Most APIs we audit cluster in the 30s and 40s — clean enough for a human, ambiguous enough that agents stumble. The leaders pull away because they fixed it on purpose.
Why APIMatic
Other tools run checks. We hand you the fix.
Twelve years of generating SDKs, docs, and tools from real-world OpenAPI definitions sit behind this audit — three independent methods, layered so each one covers the others' blind spots.
Reproducible, defensible analysis
- Thousands of deterministic rules — the same result every run.
- AI-readiness rules a linter can't catch: clarity, disambiguation, examples, completeness.
- Simulated agent scenarios run end-to-end, live over MCP — behaviour tested, not just structure.
- Mandatory blocker caps, so a broken API can't score well by accident.
Prioritisation tuned to your business
- An engineer walks the integration as a developer, a vibe coder, and an agent would.
- Competitive context against the APIs you're actually measured against.
- A board-ready roadmap your team can act on immediately.
- A 45-minute session with every audit — findings, not a sales pitch.
A linter checks structure. We watch real agents try to use your API. For the gaps we can automate, we fix them for you — generated SDKs, MCP servers, AI Context Plugins, and docs, ready the moment you are. Learn about Context Plugins →
How it works
From OpenAPI to score in 48 hours.
Free for API providers during our launch. No pitch deck, no commitment to start.
Submit your OpenAPI definition
Share your OpenAPI definition or a public API URL. Takes two minutes — no account required to start.
We run the audit
Deterministic engine, AI-readiness analysis, and live agent runs over MCP. Score delivered within 48 hours.
Review with an expert
A 45-minute session to walk the findings, prioritise fixes, and map the highest-leverage work for your team.
We use your OpenAPI only to run your audit. It's never used to train models, and we delete it on request after we deliver your report.
"APIMatic helped us prepare our platform for the future of Agentic AI."
Get your audit
See your score.
Most teams are surprised. Either way, you'll know exactly where you stand — and what to do next.
Questions