Market data APIs for AI agents.
Choose from 7 providers.

Start with the data your agent needs

A market data API gives software access to quotes, historical bars and other financial observations. Your agent can use them to write a market summary, update a watchlist or prepare research inputs. Start with the market, freshness and output you actually need.

For a US-stock prototype, evaluate Alpaca’s IEX coverage. For low-frequency research, compare Alpha Vantage. For a multi-market prototype, consider Twelve Data. For tick-level or enterprise data, evaluate the relevant Databento or Bloomberg product. These are task-based starting points, not a universal ranking.

Compare 7 market data providers

This table compares public provider products; it is not a list of integrations available in QVeris. Check the exact plan and endpoint. Public information was reviewed on September 9, 2026.

Choose around a real workflow

A US-stock watchlist

Test one symbol and the required feed before adding a long watchlist. Alpaca can be a useful IEX-based starting point; compare other products when you need different venue coverage or historical depth. Receiving an AAPL price alone does not establish full-market real-time access.

Historical research and backtesting

Compare date ranges, adjustment policies, missing periods and batch costs. Specify daily OHLCV, the timezone and whether you need split and dividend adjustments. Confirm that the selected endpoint supports the full date range.

A multi-market or institutional agent

List the instruments your workflow will actually use, then verify each one. An asset class on a product page does not imply every market is available on a free account. For tick data or market depth, also compare the streaming protocol and the service needed to consume it.

What an AAPL result should tell you

Start with one task: retrieve the latest available AAPL quote and explain its price, currency, data time and source. Label real-time, delayed or end-of-day data. If a required field is unavailable, say so.

Keep data time separate from retrieval time. Only pass the response to the next analysis step when its price definition and freshness meet your requirements. Otherwise inspect another candidate in the market-data tool directory.

Where QVeris fits in your agent

Use QVeris when you are still selecting a tool, or when one agent needs several capabilities. Discover, inspect and call tools through a consistent workflow, then connect it through MCP, CLI or an SDK.

• Discover: describe the data you need and find candidate tools.
• Inspect: check inputs, output descriptions and billing before committing to a tool.
• Call: run the selected capability and validate its response before adding it to your workflow.

If one provider and its SDK already meet your needs, direct integration may be sufficient. QVeris provides a common tool workflow; the underlying provider still determines data coverage and freshness. It does not turn every response into a normalized, licensed real-time feed.

Read the QVeris integration guide.

Make your first data request

For a concrete code example, start with one daily bar. The Tiingo EOD tool below uses the required ticker parameter and returns daily observations. This example is separate from the quote task: it does not stream live prices.

The existing project verified this tool’s schema and a non-empty response on September 7, 2026. Install requests, set QVERIS_API_KEY in your server environment, and inspect the current tool details before running. Execution can consume credits.

import json
import os
import requests

BASE = "https://qveris.ai/api/v1"
HEADERS = {
    "Authorization": f"Bearer {os.environ['QVERIS_API_KEY']}",
    "Content-Type": "application/json",
}

def request(path, payload):
    response = requests.post(
        BASE + path, headers=HEADERS, json=payload, timeout=5
    )
    response.raise_for_status()
    body = response.json()
    if body.get("success") is False:
        raise RuntimeError(body.get("error_message") or "Tool failed")
    result = body.get("result", {})
    if result.get("status_code", 200) >= 400:
        raise RuntimeError("Upstream provider returned an error")
    return body

try:
    response = request(
        "/tools/execute?tool_id=tiingo.core.eod.v1",
        {"parameters": {'ticker': 'AAPL'},
         "max_response_size": 8192},
    )
    data = response.get("result", {}).get("data")
    if data is None or data == [] or data == {}:
        raise RuntimeError("No data returned for this request")
    print(json.dumps(data, ensure_ascii=False, indent=2))
except (requests.RequestException, ValueError, RuntimeError) as error:
    raise SystemExit(f"Request failed: {error}") from error

Prefer the terminal? Install @qverisai/cli, run qveris login, then qveris discover "AAPL stock quote". Inspect a suitable search result before using its actual parameters. See the CLI reference or MCP setup guide.

Understand what free access includes

A free API key, a recurring free allowance and one-time trial credits are different offers. Compare per-minute and daily limits, endpoint costs and data freshness. Direct-provider allowances do not automatically apply to QVeris calls.

For example, Twelve Data meters API credits, which are not always one credit per request. Alpaca Basic provides IEX stock coverage. Alpha Vantage’s real-time and 15-minute delayed US-stock services are premium. The linked official plans in the table provide the current details.

Check freshness, not just response speed

Response time measures how long the request takes. Data time tells you when the price was observed. A fast response can contain yesterday’s close; outside trading hours, the latest observation may come from the previous session.

Evaluate streaming for ongoing monitoring and on-demand queries for lower-frequency research. WebSocket is a transport, not a freshness guarantee. Preserve the source timestamp, retrieval time and any fallback status in your application.

Sources and comparison method

This guide is published by QVeris and summarizes official provider documentation and pricing reviewed on September 9, 2026. It is not a seven-provider latency benchmark. Candidate recommendations reflect task fit; tool availability in QVeris must be checked separately.

Use the official links in the comparison table to confirm plan details. For the daily-price example, refer to Tiingo EOD documentation. For QVeris access and billing, see our documentation and pricing.

Frequently asked questions

Try another everyday question

Try your first market-data task

This opens a prefilled task. Review the run mode and cost in Playground before executing. Results depend on the chosen tool, account access and market session.