Alpha Vantage Pricing Compared: Daily Data for 1 QVeris Credit

For the Alpha Vantage daily time-series tool on QVeris, one call currently costs 1 credit. In our October 21, 2026 test, retrieving AAPL and MSFT used one call each and 2 credits in total, confirmed in final usage records.

This free stock API comparison focuses on two ways to access data: using Alpha Vantage directly, or using an Alpha Vantage tool through QVeris. Compare the free allowances, request limits and costs after the allowance is used. The data provider remains Alpha Vantage in the tested workflow.

The price above applies to Retrieve Daily Time Series. Other Alpha Vantage endpoints and other providers can have different billing rules. Direct free access is still a valid option for eligible requests within its allowance.

The task was deliberately small: fetch daily OHLCV for AAPL and MSFT, then prepare a side-by-side view from the returned data. Each request used TIME_SERIES_DAILY, outputsize=compact and datatype=json. No retries or additional data endpoints were used.

One call is not one daily record. In this test, a compact response contained 100 records for one symbol. Selecting the latest 5 rows or comparing the two returned datasets locally does not require another provider call.

For the same two eligible daily requests, Alpha Vantage’s direct free tier may also cost $0. QVeris adds a consistent place to inspect the tool, run the task and review its credit usage.

For this daily-series tool, the planning formula is simple: credits = symbols × runs × 1 credit. Keep measured charges and future estimates separate. A chat message that requests several symbols or data types can trigger multiple calls.

What does a credit mean in dollars?

The QVeris pricing page currently lists Pro at $19 for 10,000 credits, a displayed overage rate of $0.002 per credit, and Scale top-ups from $1 with no monthly commitment. A $100 Scale package lists 52,500 credits. These are different purchase options, so there is no single universal dollar value for every credit.

Allocating the $19 Pro purchase across 10,000 included credits gives $0.0019 per credit: $0.0038 for our 2-credit test, or $2.09 of credits for the 1,100-credit monthly example. The latter uses 11% of that $19 purchase and leaves 8,900 credits. These are consumption values, not standalone checkout prices; purchase and renewal terms still apply.

Compare a direct subscription with monthly calls × credits per call × your effective cost per credit. Then check whether both routes meet the same data, peak-rate and usage-rights requirements. Do not use a credit estimate alone to select a production plan.

The official premium page lists the following monthly tiers. Compare their capacity with the request peaks your workload actually reaches.

Checked October 21, 2026. Premium removes the standard daily cap; the per-minute limit still applies. Annual prices shown are $499, $999, $1,499, $1,999 and $2,499. Market-data access requires the applicable entitlement process. Use the current checkout terms when purchasing.

Alpha Vantage’s support page documents a general free allowance of 25 API requests per day for most datasets. It also describes special access for verified open-source or educational projects; that is not the default allowance for every account. Check the exact endpoint and output size before assuming a request is free.

QVeris lists 1,000 one-time trial credits after signup verification. At this tool’s current 1-credit rule, 1,000 credits would cover up to 1,000 such calls if all were eligible and the credits were used only on this tool. This is arithmetic, not a daily renewal or an unlimited-data promise.

The QVeris pricing page lists 10 requests/min for Free and 100 requests/min for Pro. Tool access, provider constraints and account terms still apply. Discover and Inspect are free; execution follows the selected tool’s billing rule. See QVeris plans and trial terms.

A useful financial-data workflow needs more than a low unit price. It needs a way to find the right endpoint, understand its inputs, run it and account for the result. QVeris brings these steps into the same tool workflow.

• Start from the exact tool. The daily-series detail page exposes parameters and a call price, so you can evaluate the request you actually intend to make.
• Budget a completed task. Two stock symbols require two calls in this example. Adding statements or news creates extra steps with their own prices.
• Keep a record of the spend. Usage history separates requested amounts from final charges, making a small test reproducible.
• Extend the workflow when needed. Discover other financial capabilities through QVeris and inspect their contracts before including them. A new source should earn its place in the task budget.

Explore the Alpha Vantage provider profile for related tools, or use financial-data discovery when the workflow needs another source. Each additional capability can be evaluated against the same task budget.

If the gap is data coverage rather than billing, compare alternatives for that specific requirement. The original shortlist includes Twelve Data, Finnhub, Financial Modeling Prep and Alpaca. Their current capabilities and prices require a separate evaluation; this page does not rank them from an unrun benchmark.

Alpha Vantage offers an official MCP server. QVeris also documents MCP setup and a capability-call API. Choose the integration that fits where the task will run, and keep the same symbol set, parameters and budget during evaluation.

MCP is an integration interface, not a different credit policy or a guarantee of unrestricted market-data rights. The tested tool price remains a property of the selected capability; adding an AI client can introduce separate model or platform fees.

Our two calls returned daily observations, with a last-refreshed date of October 20, 2026. The selected endpoint returns raw, as-traded data. Use adjusted data when the analysis needs corporate-action adjustments, and inspect that endpoint’s cost separately. Alpha Vantage daily-series documentation.

Realtime and delayed US market data have separate entitlement requirements. A successful request does not establish permission for commercial display or redistribution. Confirm those requirements with the provider before expanding this example into a customer-facing application. Official market-data policy.

1. Open Retrieve Daily Time Series and review the current call price.
2. Use AAPL as the symbol, daily series as the function, and compact JSON output. Sign in if execution requires it.
3. Run one request and inspect the returned dates and OHLCV fields. Our measured charge for this step was 1 credit.
4. Repeat once for MSFT for the two-symbol comparison. Inspect Usage to confirm the final total, and reuse the returned data for analysis.

{
  "function": "TIME_SERIES_DAILY",
  "symbol": "AAPL",
  "outputsize": "compact",
  "datatype": "json"
}

Start with the same two symbols and a 2-credit tool budget. The prepared task checks the current price, retrieves daily data and reports the call costs.