Service · Agent-Ready Web
AI agent-ready web infrastructure
Find out whether autonomous software can discover, understand and use your public services — then build the layers that are missing.
Why it matters
An agent that wants to do something on someone's behalf — compare, check availability, request a quote, book, pay — needs more than well-written pages. It needs predictable structure, accessible forms, and ideally a documented API with clear authentication, errors and limits.
We build this for ourselves: MakeMeMoneyNoMistakes serves an OpenAPI description, an RFC 9727 API catalog, an MCP server listed in the official MCP Registry, machine-readable pricing and error contracts, and accepts machine payments over x402.
Four levels of machine readiness
Crawlable is not the same as usable.
- L1
Crawlable
AI crawlers and agents can fetch the content.
robots policy · no accidental blocking · server-rendered HTML
- L2
Understandable
AI systems can interpret it accurately.
semantic HTML · clear entity facts · structured data · consistency
- L3
Interactive
Agents can search, compare or request.
accessible forms · stable URLs · documented API · OpenAPI
- L4
Transactable
Agents can reliably complete a transaction.
agent auth · idempotency · errors · limits · payments · observability
Each level builds on the previous one, and each costs more to implement. See the four levels worked through an example →
Scope
What's included
Audit
- Agent accessibility audit with real browser agents
- Accessibility-tree inspection; Lighthouse Agentic Browsing checks
- Forms, labels, focus order, and challenges that block legitimate agents
Describe
- Semantic HTML and machine-readable page improvements
- Public API documentation, for humans and agents
- OpenAPI creation, linting and examples
- API discovery: /.well-known/api-catalog and Link headers
Interact
- Structured, paginated catalogs where useful
- MCP servers — only where there are real actions worth exposing
- Auth and error contracts; Retry-After; idempotency
Operate
- Access policy and rate-limit design
- Agent identity signals (verified bots, signed agents)
- Endpoint observability and abuse controls
- Scripted agent interaction tests
Deliverables
What you receive
- Readiness scorecard across the four levels, with evidence
- A gap plan: what to build, in what order, at what effort
- Implementation, if engaged: OpenAPI, catalog, docs, MCP server, tests
- Agent interaction test report
Measured outcomes
What we report
- Readiness checks passed at each level, before vs after
- OpenAPI lint errors reduced to zero; example coverage
- Task success rate in scripted agent tests
- Identified agent requests and error rates, kept separate from human and unclassified traffic
How we work on this
Most businesses need Level 2. Many benefit from Level 3. Level 4 is for businesses whose customers' agents will actually buy or book. We'll tell you which applies to you.
Emerging conventions — llms.txt, WebMCP, agent commerce protocols — are implemented only with a written note of their purpose, limits and maintenance cost.
What we won't promise
- That third-party agents will adopt your service — discoverable isn't the same as adopted
- Changes to payment or authentication flows without your security review
Related services
Start with an assessment.
A fixed-scope review of your domains, search infrastructure, AI discoverability and agent readiness — with prioritized findings and a plan you can act on.