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Deploying an AI tool and getting people to use it are separate problems. In a first-person DEV Community account, a builder named Oleksandr said he deployed 35 MCP servers in 10 days, added two paywalled services and a Google Sheets add-on, yet had no active users or revenue at the point he described. His experience is a useful case study in a basic but often overlooked distinction: payment options can collect money from users, but they do not create demand or help users discover a tool.
What the builder deployed—and what happened next
Oleksandr reported building 35 MCP servers, a Google Sheets add-on and an x402 payment setup. The servers covered categories such as validators, parsers, extractors and domain-specific tools. Two Cloudflare Workers—an HS Codes Classifier and a Document-to-JSON service—used x402 paywalls, with payments settling in USDC on Base.
He also described a Sheets custom function, =HSCODE(A2), that called the classifier Worker and cached results locally. The idea was to offer a familiar route for spreadsheet users who might not want to configure an API or MCP client.
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Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →At the time of the account, he said the services worked as configured but had no active users and had generated no revenue. These are the author’s reported results, not an independently audited assessment or evidence that MCP marketplaces or agent-payment systems generally fail.
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Three monetization models, with different user friction
The account describes three options that could coexist on a server. The figures below are the author’s article-time terms; they should not be treated as current listings or offers.
| Model | Reported terms | What the model asks of a user | Revenue pattern |
|---|---|---|---|
| Free tier | 50 calls per day for each server, according to the author | Try the tool without paying first | Free usage does not itself generate revenue |
| Marketplace subscription | Pro tier reported at $19 per month for 5,000 calls, with a marketplace API key and uniform billing | Choose a subscription and use the marketplace’s billing setup | Recurring subscription revenue, subject to subscribers and usage terms |
| Pay per call | $0.01 for a single operation or $0.05 for a batch of up to 100 items, with settlement in USDC on Base | Have an agent or user initiate a paid operation | Usage-dependent transaction revenue |
The author said the IBAN validator offered free, subscription and x402 options. That illustrates how models can be layered, but the account supplies no conversion data showing that one approach performed better. All three still depend on people finding a reason to use the service.
Why a working paywall can still earn nothing
A pay-per-call system can make payment possible without making a tool desirable, discoverable or easy to invoke. For an agent to pay, it must have a relevant task, access to the tool and a reason to choose it over alternatives or a different workflow. A human user faces the equivalent challenge: they need to encounter the service, understand what it does and decide it solves a problem worth paying to solve.
Oleksandr summarized the gap as “Configuration is not distribution.” In his account, SEO, pricing and marketplace listings gave potential traffic somewhere to land, but did not automatically bring visitors. He also wrote that “x402 doesn’t sell itself.” These are conclusions from one builder’s experience, not measurements of the market as a whole.
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The practical implication is to treat distribution as a product task, not a finishing step after implementation. A server can be technically complete while its intended users still lack a clear path to find, evaluate and use it.
Lower-friction access: make the tool fit the user’s workflow
The Sheets function was the builder’s example of reducing setup for a non-developer. A logistics manager already working in a spreadsheet could enter a function such as =HSCODE(A2) instead of first setting up an API endpoint or MCP client. The account describes the add-on as calling the same Worker and caching results locally; those implementation details are the author’s claims.
This approach points to a broader design question: what is the simplest interface that reaches the intended user where they already work? An MCP server may suit an agent workflow, while a spreadsheet function may better fit a user handling tabular classification tasks. The right interface depends on the job and audience; the account does not establish that the Sheets version attracted users.
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Distribution experiments the author proposed
The proposed next steps were experiments, not reported successes. Each addresses a different point in the path from a tool to a user.
Create pages for specific searches
Rather than relying only on a broad product or marketplace listing, Oleksandr suggested programmatic pages for long-tail queries, such as HS codes for named objects or country-specific IBAN validation. The premise is to match a page to a concrete problem someone may already be searching for. The account does not report traffic or conversions from these pages.
Reach communities where potential users already gather
He named DEV.to, Medium, Reddit communities, Hacker News and AI-agent Discord communities as possible places to introduce the tools. Being present in a channel is not the same as converting its members: a useful post still needs to make the problem, audience and next step clear. The account does not show that these channels produced users.
Set a first-user goal
The author’s stated next goal was to get the first 100 users to see the tools. That is a visibility target, not evidence that 100 users adopted or paid for them. For a builder facing zero traction, separating exposure from activation and payment can make the next experiment easier to interpret: reach the right people, see whether they try the tool, then learn whether they return or pay.
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The account also includes implementation details that may help frame debugging, but they should be treated as this builder’s observations rather than universal or current platform rules.
- Worker-to-Worker calls: Oleksandr said a public
fetch()from one Worker to another did not arrive because of Cloudflare loop protection, and that a Service Binding solved the call path in his setup. - Repeated classification requests: He described caching results in KV using a SHA-256 hash of a normalized description as the key.
- Secret changes: He reported that a secret update sometimes required another deployment before taking effect.
These specifics explain issues he encountered; the account alone does not establish how Cloudflare behaves in every configuration or what current platform documentation recommends.
What this case study does—and does not—show
The account is strongest as a reminder to separate shipping from reaching customers. It records one builder’s report of a substantial implementation effort alongside no users and no revenue at the point described, plus proposed ways to reduce friction and test distribution.
It does not establish that any of the three payment models is generally superior, that a particular channel converts, or that the reported prices remain available. Its most useful question for another builder is therefore not simply how to add a paywall, but whether a specific audience has a recurring problem, can discover the tool and can use it with little enough friction to come back.
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