A developer publishing under the name ScriptMasterLabs has described a market-data endpoint that charges per call instead of by monthly subscription, in a first-person post on dev.to. The author says the service returns what he calls 55-bar cycle coordinates and volume footprint proxies for US equities, priced at $0.02 per request and settled in USDC on Base through the x402 v2 payment scheme. He states the endpoint is live and frames the release around a gap he says he searched for and could not find: computed cycle data sold per call to software agents.
The post is a community submission, so every product claim in it is the author's own. Nothing in the supplied evidence independently verifies the endpoint's output, uptime, accuracy or real-world pricing. What the evidence does contain is the author's stated design, the payment flow he documents, and his comparison of per-request billing against incumbent subscription data providers.
The author's commercial argument begins with a contrast. Footprint and order-flow analytics are, in his description, a mature industry for human traders, yet he contends no equivalent maturity exists for bots. He names Sierra Chart, Quantower, ATAS, Bookmap and Jigsaw as desktop platforms in a market he prices at $16 to $879, with Level 2 data feeds underneath running $30 to $200 per month, and NinjaTrader add-ons at $55 monthly or $459 for a lifetime. The source does not break the $16–$879 span down by individual platform, so those figures should be read as a market-wide range rather than a price for each named product. His position that no API delivers computed cycle coordinates or footprint proxies per request at any price rests on his personal searching, not on a documented survey.
He extends the comparison to mainstream market-data APIs, citing Massive/Polygon at $29 to $2,499 per month, Alpaca at $99, Finnhub from $49.99, Twelve Data from $29 and Alpha Vantage from $49.99. His specific complaint concerns free tiers: he says Massive allows 5 requests per minute with a monthly cap, and that Alpha Vantage advertises 25 calls per day but throttles to 5–7 in practice. These figures are the author's characterizations and were not independently checked for this report.
The post also positions the new endpoint against existing per-request data services, which he says are concentrated in crypto. He cites CoinGecko at $0.0005 per call on SerenAI, quoting 2,998 agent transactions in the first weeks and an argument that an agent would need 258,000 calls per month before a $129 monthly subscription becomes cheaper. He also cites Oracle Sentinel on Solana with /signal at $0.01, /whale at $0.02 and /analysis at $0.03. He names FlashAlpha, offering pre-computed GEX/DEX/VEX exposure analytics at free, $79, $299 and $1,499 per month tiers, as the closest existing model, and notes it remains a subscription.
Mechanically, the author documents a two-step payment flow. A first request to the cycle-telemetry endpoint returns an x402 v2 challenge specifying scheme "exact", network eip155:8453, an amount of 20000 in the smallest unit of the named USDC asset contract, a payTo address and a 120-second maximum timeout. The calling agent then signs an EIP-3009 transferWithAuthorization, retries with a PAYMENT-SIGNATURE header, and receives the computed coordinates. The author says the CDP facilitator sponsors gas, so an agent needs USDC but not ETH to transact.
Two design decisions are described in detail. First, the endpoint returns derived coordinates rather than raw tick data: the author says the underlying OHLCV never leaves the server, which he presents as a way around exchange redistribution licensing that he says kills most market-data startups. Second, every response reportedly carries dataSource, computedAt, barsUsed and a content hash for provenance. The author explicitly labels the methodology as daily-bar proxies rather than tick-level data, a limitation he says is stated on every response.
The author also describes a fail-closed payment model: a bad symbol returns a no-charge error, a data-source outage returns a no-charge error, and in any failure case the payment never settles. He states that every error path returns either a 402 or a no-charge response, so the rail cannot take money without delivering data. This is a design claim from the author; the evidence does not include third-party testing of the error paths.
The buy-versus-build arithmetic is the author's main pitch to bot developers. He estimates $30 to $200 per month for data plus $36 to $879 for a platform plus engineering time to compute metrics in-house, and argues that a bot scanning 50 symbols in a morning would exhaust a free tier quickly. At $0.02 per call, he says that scan costs $1.00, and a bot scanning weekly would pay about $4 per month instead of $29 to $199. He also references an r/algotrading consensus that useful historical tick datasets are rarely available without meaningful limits, and that traders stitch together two or three providers while fighting look-ahead bias.
The author names two sibling products on the same payment rail: a scraper proxy at $0.01 per scrape, which he says undercuts a SerenAI Firecrawl resale by roughly 25 percent, and an MCP gateway at $0.05 per call with a free tools/list method. He says both use the same fail-closed model and the same manifest. The post identifies the builder as a service-disabled veteran-owned small business.
For freelance developers and small teams building trading or analytics bots, the practical relevance is the pricing shape rather than the specific indicator. Per-request billing removes the fixed monthly commitment that makes low-volume or bursty bot workloads expensive, and the documented x402 flow shows a working pattern for metered API access paid in stablecoins without a subscription account. Developers evaluating this specific endpoint should treat the accuracy of the cycle coordinates and footprint proxies as unverified: the author himself labels them daily-bar proxies, not tick-level measurements, and no independent benchmark appears in the evidence.
Several questions remain open. The evidence does not state when the endpoint went live beyond the author's "live today" phrasing, nor does it give request volumes, latency figures or an uptime history. The comparison prices for competitors are the author's own and may be out of date or selectively chosen. The claim of zero per-request competitors rests on a personal search with no described method. Whether the derived-coordinates approach genuinely avoids exchange licensing obligations is a legal question the post asserts but does not substantiate.
The broader signal for this audience is that agent-facing, metered data services are being built and marketed on crypto payment rails by small operators, with provenance metadata and fail-closed billing used as trust substitutes in the absence of brand recognition. That pattern is worth watching for developers who need occasional computed data without a subscription, provided they verify output quality themselves before wiring it into anything that trades.