Start an AI Agent Readiness Rating Agency

Why AI Agents Are Your New Most Important Customer

Every day, thousands of developers open ChatGPT or Claude and type prompts like “set up a small business invoicing workflow” or “build a customer support ticketing system for my team.” They expect the AI to handle the heavy lifting — and in most cases, it does. But here’s the detail most SaaS founders miss: the AI agent making the tool selection isn’t the human typing the prompt. The agent is the actual buyer, and if your SaaS isn’t built for agents to find, access, and use it, you’re invisible to a fast-growing segment of customers.

Human buyers care about polished UI, sales calls, and brand reputation. AI agents care about machine-readable docs, public APIs, and clear authentication flows. As AI agents become more integrated into daily workflows, they’re driving a growing share of SaaS adoption, especially among developer and small business teams that rely on AI to build internal tools. Ignoring this audience isn’t a “future problem” — it’s a current revenue gap.

The Agent Readiness Rating Framework Reshaping SaaS Benchmarks

Until recently, there was no standardized way to measure how well a SaaS product works for AI agents. Gartner ranks tools for CIOs, G2 aggregates human reviews, and ESG ratings serve investors — but nobody was rating software for its newest, fastest-growing user base: AI agents. That gap led to the creation of a dedicated independent Rating Agency focused exclusively on agent readiness, using only publicly verifiable data to avoid bias or pay-for-grade rankings.

This Rating Agency has cataloged and rated more than 11,000 SaaS and MCP services to date, and has probe-tested 2,257 of them with real JSON-RPC handshakes, logging 3,475 successful connections out of 4,367 total attempts. It recently evaluated 200 leading Japanese SaaS products to test how many could be accessed and used by an AI agent out of the box. The results were stark: only 41 products (20.5%) earned an A rating or higher, with just 11 hitting the top AAA tier. Ratings run from AAA to D, with the full evaluation formula published publicly to ensure transparency.

The Five Core Metrics for Agent Readiness

The evaluation framework measures performance across five non-negotiable pillars, all focused on what an agent can verify without human intervention:

• AI Access: Does the product offer a public, well-documented API or official MCP server that an agent can connect to without jumping through hoops like sales calls or gated access requests?
• AI Discoverability: Can an agent find and parse your developer documentation, llms.txt files, and structured data without hitting login walls or blanket robots.txt rules that block AI crawlers?
• AI Execution: Can an agent complete full end-to-end tasks using your tool, from authentication to final output, without any human hand-holding?
• AI Trust: Are authentication flows, permission scopes, and delegation safety rules clearly documented so an agent can operate securely without risking data leaks?
• AI Compatibility: Does your tool behave consistently across different AI models and agent frameworks, with no unexpected breaking changes that derail workflows?

What the Top-Performing SaaS Products Get Right

The 41 products that earned an A rating or higher share a consistent profile that any SaaS team can replicate. The top 11 AAA-rated products all go a step further, treating agent accessibility as a first-class product feature rather than an afterthought.

• They ship an official MCP server or fully public, well-documented API that requires no sales contact to access. The AAA tier is dominated by teams that built their MCP server using official tooling like the Anthropic MCP SDK, and update it in lockstep with their core product.
• Their developer documentation is openly accessible to non-browser user agents, with no login walls, gated PDF requests, or rules that block AI crawlers from reading docs. Many top performers even publish dedicated llms.txt files to make their content easier for agents to parse.
• Their authentication flows are simple enough to explain in a single page, with clear OAuth scopes and no bespoke, overly complex token ceremonies that agents can’t parse. Standard OAuth 2.0 flows outperform custom auth setups 9 times out of 10 in agent testing.

Why 80% of SaaS Products Fail the Agent Readiness Test

The 159 uncertified products don’t fail on dramatic, obvious flaws. They fail on small, quiet barriers that block agents from accessing their tools, most of which are easy to overlook if you’re only optimizing for human users.

• Developer documentation returns 403 or 404 errors when accessed by non-browser user agents, meaning agents can’t read the docs to learn how to use the tool. You can test this yourself with tools like Postman to see how your docs perform for non-browser requests.
• API
• Inconsistent API behavior across different models or agent frameworks, leading to failed tasks and broken workflows for end users who rely on agent recommendations.

A common, often overlooked pattern among failing products is that they prioritize human-facing onboarding flows over machine-readable access points, assuming that agent adoption is a future problem rather than a current one.

How to Use Agent Readiness to Drive Revenue (Or Build a Service Business)

Whether you run a SaaS product or offer AI-related services, the agent readiness gap is a massive opportunity to generate revenue.

For SaaS Founders

Many teams that have made these small changes report a 25-40% increase in signups from developer teams using AI to build workflows, as agents start recommending their tool as a default option for relevant tasks.

For Service Providers

There’s a huge, underserved market for agent readiness audit and optimization services. Most small and mid-sized SaaS teams don’t have the expertise to evaluate their own agent accessibility, and they’re willing to pay for help. You can build a standardized audit service using the five-pillar framework, then sell it on platforms like Upwork or Fiverr to SaaS clients. For higher-ticket clients, you can offer full optimization packages that include building custom MCP servers, restructuring documentation for agent readability, and setting up ongoing monitoring to ensure compatibility across AI models.

You can also package smaller, fixed-price audits as digital products on Gumroad, targeting solo SaaS founders who can’t afford a full agency retainer. Basic audits typically sell for $500 to $2,000 per client, with ongoing monitoring adding $200 to $500 in monthly recurring revenue per account. As AI Agents become a larger share of the buyer market, demand for these services will only grow.