How AI reads Mr. Handyman

mrhandyman.com Jun 9, 2026 6 min read Basic Web Presence

Short

37/ 100

AEO Level 2Basic Web Presence

The short answer

Mr. Handyman scores 37 out of 100 on our AEO scan, placing it at level 2. The site's content structure is solid at 70, but agent interfaces and identity authentication both register zero — meaning AI assistants can read the text but cannot interact with or verify the business as a trusted service provider.

What AI sees

When an AI agent visits Mr. Handyman's homepage today, it encounters a well-organized home repair franchise with readable content but no explicit guidance for automated discovery.

AI crawlers land on a homepage describing residential and commercial handyman services across franchise locations. The content structure score of 70 suggests headings, service categories, and location information are reasonably parseable for a home services brand. However, no robots.txt directives address AI crawlers specifically — GPTBot, ClaudeBot, and PerplexityBot receive no explicit instructions whatsoever. There are no Link response headers pointing agents toward structured resources, no Markdown endpoint for content-only responses, and no machine-readable API catalog. Structured data is partial at 40, meaning some schema markup exists but agent discovery mechanisms are entirely absent, leaving automated systems to improvise rather than navigate with confidence.

Mr. Handyman homepage as seen by an AI crawler — organized service layout with no agent discovery headers or Markdown endpoint detected

robots.txt inspection showing zero AI crawler directives — GPTBot, ClaudeBot, and PerplexityBot receive no explicit rules

Where it loses points

Agent interfaces and identity authentication both score zero — the most critical gaps preventing AI systems from treating Mr. Handyman as a trustworthy, interactable service provider.

How to fix it

Three targeted server-level changes would immediately improve how AI agents discover, parse, and recommend Mr. Handyman across answer engines and AI assistants.

AI Crawler Rules in robots.txt

Goal

Declare explicit per-agent rules so AI crawlers know exactly which paths they may index and cite.

Issue

The current robots.txt contains no user-agent blocks for GPTBot, ClaudeBot, PerplexityBot, or any other AI crawler.

Fix

Add individual user-agent sections for GPTBot, ClaudeBot, PerplexityBot, and similar bots with explicit Allow directives covering service pages, location pages, and FAQs. This signals crawl consent to AI systems and prevents accidental exclusion from AI-generated local service answers.

MCP Server Card

Goal

Publish a machine-readable server card so AI agents can automatically discover capabilities and endpoints.

Issue

No MCP Server Card exists at /.well-known/mcp/server-card.json.

Fix

Create /.well-known/mcp/server-card.json containing serverInfo with name, version, and description fields, a transport endpoint, and capabilities covering service lookup and location finder. This allows AI assistants to surface Mr. Handyman offerings as structured, actionable responses rather than generic text citations.

Markdown for Agents

Goal

Return clean Markdown content when AI agents request it via the Accept header.

Issue

The site returns HTML even when requests include Accept: text/markdown, forcing agents to parse full markup rather than clean prose.

Fix

Intercept requests carrying Accept: text/markdown and respond with Content-Type: text/markdown, stripping navigation, footers, and promotional elements — delivering service descriptions, pricing context, and location details as clean prose. This measurably improves citation quality and relevance in AI-generated home repair answers.

Common questions

Does Mr. Handyman appear in AI-generated answers from ChatGPT or Perplexity?

Possibly, but inconsistently. Without explicit AI crawler rules in robots.txt, crawlers may index the site opportunistically or skip it entirely. Adding GPTBot and PerplexityBot directives signals clear consent, increasing the likelihood of accurate, citation-ready appearances when users ask AI assistants about local handyman or home repair services.

What does an AEO score of 37 mean for a home services franchise?

A score of 37 places Mr. Handyman in the early adoption tier for answer engine optimization. Content structure is above average for the industry, but the complete absence of agent interfaces means AI assistants cannot programmatically query services, availability, or locations — a growing disadvantage as AI-first local search behavior accelerates.

How quickly could Mr. Handyman improve its AEO score?

The fastest gains come from robots.txt updates and adding /.well-known/ endpoints — both are server-level configurations requiring no site redesign. Implementing AI crawler rules, an MCP server card, and a Markdown response endpoint could realistically push the score from 37 toward 60-65 within a single focused development sprint.