FRED Economic Data Scraper

FRED Economic Data Scraper

Scrape FRED economic data series by search term, category, or frequency, up to a million per run. Each series returns its ID, title, units, seasonal adjustment, and popularity, with optional historical observations. No API key required. Export to CSV, JSON, Excel, or XML.

The FRED API requires a registered key and rate-limits requests. This scraper reads the public series catalog directly, letting you search by keyword, filter by category, frequency, units, and seasonal adjustment, and return matching economic data series in a flat, consistent schema. It handles pagination and optional observation fetching so you get clean data without writing a single request.

Who uses it	What they scrape FRED for
Economists	Pull the latest CPI, GDP, or employment series for a research paper.
Financial analysts	Gather interest rate and inflation series to feed into a market model.
Data journalists	Collect multiple economic indicators to fact-check a story on wage growth.
Academic researchers	Build a dataset of production and business activity series for a longitudinal study.

What it does

This Actor collects FRED economic data series metadata by search query or category ID and returns each series as a flat row, with optional historical observations.

• 🔍 Full-text search: Find series by keyword across titles, units, frequency, and tags.
• 📂 Category filter: Restrict results to a specific FRED category like National Accounts or Prices.
• 📊 Observation download: Optionally fetch every historical date-value pair for each matched series.
• 📋 Fixed schema: Every series row has the same fields, ready for CSV, JSON, Excel, or XML export.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with FRED data

📈 Monitor inflation indicators.

An economist searches for 'cpi' with monthly frequency and seasonally adjusted units to track consumer price changes over time.

🏭 Track production and business activity.

A researcher filters by category ID 1 and frequency 'Monthly' to collect industrial production series for a manufacturing report.

💼 Build a labor market dashboard.

A financial analyst pulls all unemployment-related series, sorted by popularity, to feed a weekly jobs market update.

📚 Gather data for academic research.

A PhD student collects GDP and national accounts series with full historical observations for a macroeconomics dissertation.

Why choose this scraper

	What you get
No API key	Reads the public catalog without registration or rate limits.
Flexible filtering	Combine search text, category, frequency, units, and seasonal adjustment in one run.
Observation data	Optionally pull the full time series of date-value pairs for each series.
Sort control	Order results by popularity, last update, observation range, or search rank.

How it compares

No other Store actor targets FRED the same way, so the honest comparison is with the alternatives teams actually weigh.

	FRED Economic Data Scraper	Build it in-house	By hand
Setup	Run it now, zero config	Days of engineering	None, but hours per pull
When FRED changes	Maintained for you	You fix it	You re-learn the page
Proxies, retries, anti-bot	Built in	Your problem	Browser only
Output	Fixed JSON schema, CSV/Excel export	Whatever you build	Copy-paste
Cost	Pay per result	Engineering time	Analyst hours

Configure the run

Drive the Actor with a search term or a category ID, then narrow results by frequency, units, and seasonal adjustment before the data reaches your dataset. The Input tab lists every parameter.

A first run with the defaults:

{
  "maxItems": 10,
  "searchText": "cpi"
}

A larger pull:

{
  "maxItems": 200,
  "searchText": "cpi"
}

Pricing

Pay-per-result: $0.0075 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$0.75
1,000 results	$7.50
10,000 results	$75.00

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the FRED Economic Data Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to FRED through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/fred-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

I am getting no results for my search term.

Try a broader or shorter keyword. FRED search matches against series titles, units, and tags. Check that your frequency, units, or seasonal adjustment filters are not too restrictive and excluding all matches.

The run is taking a very long time.

If you have 'Include Observations' enabled, the Actor fetches every historical data point for each series. Reduce the 'Maximum series' count or disable observations to speed up the run.

My category filter is not working.

Verify the category ID is correct. You can find the numeric ID at the end of the category URL on the FRED website. Also, ensure you have not combined it with a search term that returns no results within that category.

The sort order seems wrong.

Check the 'Sort Order' and 'Order By' fields. The default is 'search_rank' in descending order. If you change the sort field, make sure the direction is set as you expect.

FAQ

Question	Answer
Do I need a FRED API key to use this scraper?	No. This Actor reads the public FRED web catalog directly, so you do not need to register for an API key or worry about rate limits.
What is the difference between series metadata and observations?	Series metadata includes the title, ID, units, frequency, and seasonal adjustment. Observations are the actual historical date-value pairs. You can choose to include observations by checking the 'Include Observations' box, but it will increase the run time.
How do I find the right category ID?	You can browse categories on the FRED website. The ID is the number in the URL. For example, category ID 10 is National Accounts, and ID 1 is Production & Business Activity.
Can I search for multiple terms at once?	The search text field accepts a single query string, which FRED uses for a full-text search across series titles, units, and tags. For multiple distinct searches, run the Actor multiple times with different terms.
Why does fetching observations take so long?	Each series can have decades of daily, weekly, or monthly data. The Actor fetches all historical observations for every matched series, which requires a separate request per series and can take several minutes for large result sets.
What export formats are supported?	You can export your results to CSV, JSON, Excel, or XML directly from the Apify dataset.
How many series can I collect in one run?	You can set the maximum up to 1,000,000 series. The Actor will stop when it reaches that limit or when there are no more matching series.
Can I filter by seasonal adjustment?	Yes. You can choose 'Seasonally Adjusted' or 'Not Seasonally Adjusted' from the dropdown to narrow your results.

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Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Federal Reserve Bank of St. Louis. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.