# Agent-ready websites for marketing teams

// service / agentic-web

Make your website discoverable by AI agents. Not just AI crawlers. Schema, Model Context Protocol (MCP) endpoints, and a Markdown-for-bots edge layer, live. We run this on our own site. That's the proof.

**Primary CTA:** Book a 20-minute call
**Secondary:** See the receipt

## Your site was built for the wrong audience.

Everyone's talking about AI agents browsing the web. Very few sites are actually ready for it. Your current site was designed for humans skimming and Googlebot indexing. Neither of which matches how Claude, ChatGPT, or a customer's own agent will consume it.

The gap shows up in three places: missing AI citations when prospects ask in-category questions, agentic workflows that bounce off your site because the content isn't machine-addressable, and a slow erosion of organic visibility you'll only measure after it's gone.

The fix isn't a rebuild. It's a layer (schema, endpoints, and edge middleware) that sits in front of what you already have.

## We ship live infrastructure, not pledges.

- **Content audit for AI consumability.** We run Skills that simulate how Large Language Models (LLMs) parse your pages and score citation-readiness per URL. Output: a ranked list of what to fix first.
- **Structured data upgrades.** FAQ, HowTo, Product, Person, and Organization schema, cross-linked as an entity graph. Not scattered one-offs. A connected graph agents can walk.
- **Agent-readable endpoints.** REST, GraphQL, or MCP-compatible servers that expose your product, docs, and content to authorized agents. The protocol matches what Claude and agentic clients already speak.
- **Markdown-for-bots edge middleware.** At the CDN, we detect AI user agents and serve clean Markdown instead of HTML. This is what `llms.txt` pretends to be. We run it on this site.
- **Embedded assistants.** Optional. Claude-powered or GPT-powered agents embedded in your site for lead qualification, support, or product search. Deployed where they're needed, not everywhere at once.

### Why not llms.txt?

`llms.txt` is a pledge, not a feature. There's no version, no enforcement, no observability, and no guarantee a bot honors it. Meanwhile an edge middleware is a *live running system*: we can measure bot hits, tune what gets served, and verify behavior with one `curl` command. We ship the latter. [Inspect it yourself →](/why-markdown/)

## What you get.

- Audit report with citation-readiness score per page
- Schema implementation plan. Wired into your existing templates
- MCP server prototype where applicable (product catalog, docs, or content)
- Cloudflare, Fastly, or Vercel edge middleware deployed and documented
- Monitoring for bot traffic by user-agent. You see what's actually hitting you
- Documentation you own, in a repo you control

## The stack we deploy.

Cloudflare Pages Functions · Cloudflare Workers · MCP · schema.org · JSON-LD · Claude · Claude Code · custom GEO audit skill · DataForSEO.

## Who this is for.

Marketing leaders preparing for AI-first discovery. CTOs and engineering leaders working on LLM integration. Growth-stage companies that want an adoption-speed advantage over competitors whose teams have not yet started evaluating agentic infrastructure.

If your team is still debating whether AI search matters, start with the Strategy & Readiness Assessment. If you already know it matters and you want the infrastructure live, this is the engagement.

## For enterprise and martech marketing teams.

Technology vendors have a sharper version of this problem. Your buyers are the people most likely to shortlist with an agent, and the questions they ask are about you: which platform has the cleanest docs, which one exposes its catalog to agents, which one an agent can compare head to head. If your product pages, docs and pricing sit behind JavaScript or scatter across subdomains, the agent compares the competitor it can read.

Operationalizing MCP in your marketing is mostly plumbing, and it fits the team you already have. With an in-house team we:

- Map the questions agents get about your category and check which of your pages answer them in a form an agent can parse.
- Expose docs, product data and comparison content through an MCP server or a clean API, scoped to public content, so agents query it instead of scraping it.
- Put the Markdown-for-bots layer in front of your marketing site and docs, on the CDN you already use.
- Hand your web, content and dev teams the templates, schema and runbooks so it keeps working after the project ends.

You keep the stack, the CMS and the roadmap. We add the agent layer and the measurement, and your team gets a senior strategist plus an AI agent workforce doing the build work.

→ Book a 20-minute call: `/contact/#book-a-call`

## Frequently asked questions.

**What is an agent-ready website?**
A site that's structured so AI agents (Claude, ChatGPT, Perplexity, or a customer's own agent) can consume it natively. That means clean schema, predictable URLs, Markdown versions served to AI user agents, and optional MCP endpoints for deeper programmatic access. It's the difference between being crawlable and being usable.

**Why not just use llms.txt?**
See the callout above. Short version: `llms.txt` is a pledge, not a feature. It's a text file asking bots to behave a certain way, with no enforcement and no measurement. Edge middleware is a live running system. We measure bot hits, tune what gets served, and verify behavior with one `curl` command. We ship the latter and run it on this site.

**How do you handle privacy and abuse?**
User-agent filtering, rate limiting, and optional authentication on MCP endpoints. We serve public content to bots and keep auth-gated content behind the same auth it always had. Abuse prevention is standard Cloudflare or Fastly Web Application Firewall (WAF) tuning. Nothing exotic.

**Can you do this on our existing site without a rebuild?**
Yes. The edge middleware runs at Cloudflare, Fastly, or Vercel. In front of whatever CMS you already have. Schema goes into your existing templates. MCP servers run alongside, not inside, the site. Rebuild is almost never necessary.

**How do we measure this?**
Three data streams: bot-traffic logs by user-agent (is Claude actually hitting the Markdown version?), citation tracking against ChatGPT, Perplexity, and Claude (do we show up?), and MCP endpoint analytics (who's querying, what, how often?). You get dashboards, not vibes.

**What does it mean to operationalize MCP in marketing?**
It means your marketing content is available to AI agents through the Model Context Protocol, not only as crawled HTML. In practice that is an MCP server exposing docs, product data and comparison content to authorized agents, a schema graph on the public site, and logging so you can see which agents query what. For most marketing teams the first version covers public content only and runs alongside the site.

**Do you work with our in-house marketing and web teams, or replace them?**
We work alongside them. Your team keeps the CMS, the roadmap and the brand. We scope the agent layer, build the MCP server and edge middleware, wire schema into your templates, and hand over docs and runbooks your developers can maintain. Most engagements start with the Agent-Ready Audit so both teams agree on what to fix first.

## Related

→ Receipt: `/our-work/agent-ready-infrastructure-for-winstondigitalmarketing-com/`

## CTA

**Ship an agent-ready site in 60 days.** We audit, wire the schema, deploy the edge middleware, and ship an MCP endpoint where it matters. You get the infrastructure and the docs. No rebuild required.

→ Book a 20-minute call
→ Or run the free audit first