# DBnomics Economic Series Scraper (`parseforge/dbnomics-economic-series-scraper`) Actor

Scrapes economic time series from DBnomics by series ID, custom ID, or keyword search. Returns each observation as a flat row with period, value, and metadata. Supports ECB, IMF, World Bank, Eurostat, OECD, and more.

- **URL**: https://apify.com/parseforge/dbnomics-economic-series-scraper.md
- **Developed by:** [ParseForge](https://apify.com/parseforge) (community)
- **Categories:** Developer tools, Automation, Other
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $9.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

[![ParseForge](https://raw.githubusercontent.com/ParseForge/apify-assets/main/banner.jpg)](https://apify.com/parseforge?fpr=vmoqkp)

### DBnomics Economic Series Scraper

**Scrape economic time series from DBnomics by series ID, dataset, or keyword search, up to a million series per run.** Every observation comes with its period, value, and metadata. No API key or registration. Export to CSV, JSON, Excel, or XML.

DBnomics aggregates millions of economic series from providers like the ECB, IMF, World Bank, Eurostat, and OECD, but its API requires you to know provider and dataset codes. This Actor resolves series by ID or search term and returns every observation in one flat row. You can pull a single exchange rate, a whole dataset, or every series matching a keyword like inflation.

| Who uses it | What they scrape DBnomics for |
|---|---|
| Economists | Pull the exact series they need for a model without writing API code |
| Financial analysts | Monitor exchange rates, inflation, or GDP across providers in one dataset |
| Data journalists | Gather comparable economic indicators for a story or visualization |
| Researchers | Build a panel of macroeconomic variables from multiple sources |

### What it does

This Actor collects economic time series from DBnomics by series ID, custom series ID, or keyword search, and returns each observation as a flat row with period, value, and series metadata.

- 🔎 **Keyword search:** type a term like inflation or unemployment and the Actor resolves matching datasets to their series and observations.
- 🆔 **Series ID or custom ID:** fetch any series with a provider/dataset/series\_code, or paste a custom code from db.nomics.world.
- 📊 **Flat observation rows:** each period and value becomes one row, ready for pivot tables or time-series models.
- 🌐 **Multi-provider coverage:** ECB, IMF, World Bank, Eurostat, OECD, and hundreds more through one interface.

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

### What you can do with DBnomics data

**📈 Track inflation across countries.**

An economist runs a search for inflation, sets maxSeriesPerSearch to 10, and gets monthly HICP and CPI series from Eurostat, IMF, and national sources to compare trends.

**💱 Monitor exchange rates daily.**

A financial analyst schedules the Actor with the ECB USD/EUR series ID and receives the latest monthly or annual average in a CSV for their dashboard.

**🌍 Build a macro panel for research.**

A PhD student pulls GDP, population, and unemployment series from World Bank and OECD by custom IDs and merges them into one dataset for a regression.

**📰 Fact-check economic claims.**

A data journalist searches for GDP growth and collects the IMF WEO series to verify a politician's statement with the official numbers.

### Why choose this scraper

|  | What you get |
|---|---|
| **No API key** | DBnomics is open, and this Actor reads the public feeds directly |
| **One flat schema** | Every observation has the same columns regardless of provider |
| **Search without codes** | Find series by keyword and let the Actor resolve the IDs |
| **Scale to a million series** | Set maxItems up to 1,000,000 for bulk collection |

### How it compares

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

| | DBnomics Economic Series Scraper | Build it in-house | By hand |
|---|---|---|---|
| Setup | Run it now, zero config | Days of engineering | None, but hours per pull |
| When DBnomics 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 from a known series ID, a custom series ID, or a keyword search, alone or together, and set limits on how many series and observations to collect. The Input tab lists every parameter.

A first run with the defaults:

```json
{
  "maxItems": 10,
  "maxSeriesPerSearch": 5
}
```

A larger pull:

```json
{
  "maxItems": 200,
  "maxSeriesPerSearch": 5
}
```

### Pricing

Pay-per-result: **$0.011 per result** collected. You pay only for the results written to your dataset.

| Results collected | Approximate cost |
|---|---|
| 100 results | $1.10 |
| 1,000 results | $11.00 |
| 10,000 results | $110.00 |

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](https://console.apify.com/sign-up?fpr=vmoqkp) to collect up to 1,000,000 results per run.

### Run it

1. [Create a free Apify account with $5 in credit](https://console.apify.com/sign-up?fpr=vmoqkp).
2. Open the [DBnomics Economic Series Scraper](https://apify.com/parseforge/dbnomics-economic-series-scraper?fpr=vmoqkp).
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](https://docs.apify.com/api/v2) (`run-sync-get-dataset-items`) or the [ApifyClient](https://docs.apify.com/api/client/js) for JavaScript and Python.

### Use with AI agents (MCP)

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

```bash
claude mcp add --transport http apify "https://mcp.apify.com/?tools=parseforge/dbnomics-economic-series-scraper"
```

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

### Troubleshooting

**Why am I getting no results?**

Check that your series ID is in the correct provider/dataset/series\_code format. If using searchQuery, try a broader term like 'GDP' instead of a specific phrase. Also ensure maxItems is at least 1.

**The run returns an error about an invalid series ID.**

Verify the series ID on db.nomics.world. Some datasets have version suffixes like IMF/WEO:2024-10. Copy the exact code from the series page.

**I get too many observations and the run is slow.**

Lower maxSeriesPerSearch or maxItems. If you only need one series, use seriesId or customSeriesId without searchQuery.

**The data seems outdated.**

DBnomics updates at different frequencies depending on the provider. Check the provider's release calendar and schedule the Actor to run after updates.

**Search returns irrelevant series.**

Use more specific keywords or combine terms. You can also find the exact series ID on db.nomics.world and use customSeriesId instead of search.

### FAQ

| Question | Answer |
|---|---|
| Do I need a DBnomics API key? | No. DBnomics is an open data platform, and this Actor reads the public feeds without authentication. |
| How do I find a series ID? | Go to db.nomics.world, browse or search for a series, and copy the provider/dataset/series\_code from the URL or the series page. You can also use the searchQuery input to find series by keyword. |
| What is the difference between seriesId and customSeriesId? | seriesId is a dropdown of common series for quick selection. customSeriesId accepts any valid DBnomics series code and overrides seriesId when both are set. |
| Can I collect multiple series in one run? | Yes. Use searchQuery to pull many series from matched datasets, and set maxItems and maxSeriesPerSearch to control the total. |
| What providers are covered? | DBnomics aggregates over 100 providers, including ECB, IMF, World Bank, Eurostat, OECD, and many national statistical offices. Any series on db.nomics.world can be fetched. |
| What format is the output? | The Actor returns a flat dataset where each row is one observation with period, value, and series metadata. You can export to CSV, JSON, Excel, or XML from the Apify platform. |
| How many observations can I get? | The maxItems input controls the number of series, up to 1,000,000. Each series can have thousands of observations, so the total rows can be very large. |
| Does the Actor handle revisions or updates? | It fetches the latest data available on DBnomics at the time of the run. Schedule the Actor to run daily or weekly to keep your dataset current. |
| Can I search in languages other than English? | The searchQuery matches DBnomics metadata, which is primarily in English, but some providers include native-language titles. Try keywords in the provider's language if needed. |
| Is there a limit on search results? | maxSeriesPerSearch limits how many series are pulled from each matched dataset, and maxItems limits the total series per run. Set them according to your needs. |

### Related actors

Browse the full [ParseForge collection](https://apify.com/parseforge?fpr=vmoqkp) 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 CEPREMAP. 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.

# Actor input Schema

## `seriesId` (type: `string`):

A known DBnomics series to fetch, in the form provider/dataset/series\_code. Pick one from the list, or use Custom Series ID below for any other series.

## `customSeriesId` (type: `string`):

Any DBnomics series, as provider/dataset/series\_code (for example IMF/CPI/M.US.PCPI\_IX). When set, this overrides the Series ID above. Find codes at db.nomics.world.

## `searchQuery` (type: `string`):

Optional keyword search (for example inflation, GDP, unemployment). The top matching datasets are resolved to their series and their observations are collected. Runs in addition to any series above.

## `maxItems` (type: `integer`):

How many series to collect per run.

## `maxSeriesPerSearch` (type: `integer`):

How many series to pull from each matched dataset when using Search Query. Higher values widen coverage but return more observations.

## Actor input object example

```json
{
  "seriesId": "ECB/EXR/A.USD.EUR.SP00.A",
  "maxItems": 10,
  "maxSeriesPerSearch": 5
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "maxItems": 10,
    "maxSeriesPerSearch": 5
};

// Run the Actor and wait for it to finish
const run = await client.actor("parseforge/dbnomics-economic-series-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "maxItems": 10,
    "maxSeriesPerSearch": 5,
}

# Run the Actor and wait for it to finish
run = client.actor("parseforge/dbnomics-economic-series-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "maxItems": 10,
  "maxSeriesPerSearch": 5
}' |
apify call parseforge/dbnomics-economic-series-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,parseforge/dbnomics-economic-series-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/hcCtfrjaChEdMABRy/builds/ROr4uHauCKhjGy6U5/openapi.json