# European Parliament MEPs Scraper | MEP Profiles and Data (`parseforge/european-mep-disclosures-scraper`) Actor
Export Members of European Parliament records from the EU Open Data Portal: full name, identifier, given/family name, sort label and label. Combine with parliamentary terms for historical mapping. CSV, Excel, JSON or XML for political research and lobbying analysis.
- **URL**: https://apify.com/parseforge/european-mep-disclosures-scraper.md
- **Developed by:** [ParseForge](https://apify.com/parseforge) (community)
- **Categories:** Other, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $19.00 / 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/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## ๐ช๐บ European Parliament MEPs Scraper
> ๐ **Export export european parliament members profiles and term data in seconds.** Export Members of European Parliament records from the EU Open Data Portal: full name, identifier, given/family name, sort label and label. Combine with parliamentary terms for historical mapping. CSV, Excel, JSON or XML for political research and lobbying analysis. No account required for the source.
> ๐ **Last updated:** 2026-05-26 ยท **๐ 11 fields** per record ยท **5K+ historical MEPs** ยท **European Union (all parliamentary terms since 1979)**
The European Parliament MEPs Scraper extracts structured records from European Parliament Open Data. Every record captures the canonical fields you would expect from the upstream source - ready for analytics, dashboards, BI tooling, or further enrichment.
The dataset spans european union (all parliamentary terms since 1979) and exposes the same data the official website publishes - normalised, paginated, and exportable.
**Who uses this data?**
| Audience | Use Case |
|---|---|
| Lobbyists | Build longitudinal datasets for analysis |
| Compliance teams | Monitor regulated entities and filings |
| Journalists | Investigate public records at scale |
| Data analysts | Power BI dashboards and reports |
| Academic researchers | Run quantitative studies on public data |
| Product teams | Embed live european parliament meps records into apps |
### ๐ What the European Parliament MEPs Scraper does
- Queries European Parliament Open Data for the latest records
- Supports targeted filtering via the input parameters (see below)
- Returns structured records with 11 fields, no scraping artifacts
- Handles pagination automatically up to your `maxItems` limit
- Cleans HTML entities and normalises dates and identifiers
- Delivers results as CSV, Excel, JSON, or XML via Apify dataset export
> ๐ก **Why it matters:** Public-data sources rarely offer bulk export. This Actor turns the live site into a queryable dataset - useful for any team that needs european parliament meps data at scale.
### ๐ฌ Full Demo
_๐ง Coming soon_
### โ๏ธ Input
Field
Type
Required
Description
maxItems
integer
No
Free users: 10. Paid users: optional, max 1,000,000.
**Example 1: Default run (preview)**
```json
{
"maxItems": 10
}
````
**Example 2: Targeted query**
```json
{
"maxItems": 3
}
```
> โ ๏ธ **Good to Know:** Free users are limited to 10 items per run. Upgrade to a paid plan to unlock up to 1,000,000 items.
### ๐ Output
| Field | Type | Description |
|---|---|---|
| ๐ ID `identifier` | string | - |
| ๐ค Name `label` | string | - |
| ๐ Given Name `givenName` | string | - |
| ๐ Family Name `familyName` | string | - |
| ๐ค Sort Label `sortLabel` | string | - |
| ๐ Open Data URL `url` | string | - |
| ๐ MEP Page `meppage` | string | - |
| ๐ Country `countryOfRepresentation` | string | - |
| ๐ Type `type` | string | - |
| ๐ Collected `scrapedAt` | string | - |
| โ Error `error` | string | Error message if record could not be retrieved |
### โจ Why choose this Actor
| Feature | Detail |
|---|---|
| ๐ No login required | Public data only - no credentials needed |
| ๐ Targeted filtering | Search by name, code, date range, type |
| ๐ 5K+ historical MEPs | Comprehensive coverage of european union (all parliamentary terms since 1979) |
| ๐งน Clean output | Dates normalised, HTML stripped, arrays flattened |
| โก Fast API | Direct source access - no browser overhead |
| ๐ Auto-pagination | Retrieves all matching results up to your maxItems |
| ๐พ 4 export formats | CSV, Excel, JSON, XML all available |
| ๐ก๏ธ Retry logic | Multi-attempt retry with backoff for reliability |
### ๐ How it compares to alternatives
| Method | Speed | Scale | Structured Output | Free |
|---|---|---|---|---|
| **This Actor** | Fast | 1,000,000 records | Yes (11 fields) | 10 free / unlimited paid |
| Manual site search | Slow | Limited per session | No | Yes |
| Bulk data download | Slow setup | Variable | Partial | Variable |
| Custom API script | Variable | Unlimited | Requires dev work | Dev cost |
### ๐ How to use
1. **[Create a free Apify account](https://console.apify.com/sign-up?fpr=vmoqkp)** - includes $5 free credit
2. Open the **European Parliament MEPs Scraper** actor page
3. Configure your input - set filters or leave defaults
4. Set `maxItems` (10 for a quick preview, higher for bulk extraction)
5. Click **Run** and wait for the dataset to populate
6. Download your results as **CSV, Excel, JSON, or XML**
### ๐ผ Business use cases
#### Compliance and Due Diligence
Teams use european parliament meps data to verify entities, monitor regulatory status, and feed KYC / AML pipelines.
#### Market Research
Analysts map european union (all parliamentary terms since 1979) to understand market structure, competitive activity, or regulatory trends.
#### Lead Generation
Sales teams enrich CRM records with european parliament meps data to identify prospects and qualify leads.
#### Investigative Journalism
Reporters use bulk extracts to find patterns, anomalies, and stories hidden in public records.
### ๐ Automating European Parliament MEPs Scraper
Connect this Actor to your existing workflows using Apify integrations:
- **Make (Integromat)** - trigger a run on a schedule and push results to Google Sheets or a database
- **Zapier** - automatically export new records to Airtable, Notion, or your CRM
- **Slack** - get notified when a monitored entity has new activity
- **Webhooks** - receive real-time notifications when a run completes
### ๐ Beyond business use cases
#### Academic Research
Study trends, behaviours, and patterns in european union (all parliamentary terms since 1979) records across time.
#### Civic Tech and Transparency
Civic-tech projects build dashboards on top of bulk extracts to surface public-interest insights.
#### Education
Educators use real european parliament meps data to teach data analysis, regulatory frameworks, and domain knowledge.
#### Personal Research
Individuals - researchers, hobbyists, family historians - use bulk export to answer questions that no single web search can.
### ๐ค Ask an AI assistant about this scraper
Have questions about how to use this Actor or interpret the data? Paste a few sample records into ChatGPT, Claude, or another AI assistant and ask it to:
- Summarise the dataset
- Explain the meaning of specific fields
- Identify patterns across a batch of records
- Suggest filter combinations for your specific question
The structured JSON output from this Actor is well-suited for AI analysis.
### โ Frequently Asked Questions
**๐ What does this Actor do?**
It extracts european parliament meps records from European Parliament Open Data into a clean, queryable dataset.
**๐ How many records are available?**
5K+ historical MEPs.
**๐ Do I need an account or API key?**
No. This Actor uses public sources that require no authentication.
**๐ How up-to-date is the data?**
The Actor queries the source live on every run, so the dataset reflects whatever is published at runtime.
**๐ Can I filter by specific fields?**
Yes - see the Input section above for all supported filters.
**โก How fast is the scraper?**
A typical 10-item preview completes in under 30 seconds. Larger runs scale linearly with the source's rate limits.
**๐ What format is the output?**
Records are stored in Apify's dataset storage and can be exported as CSV, Excel, JSON, or XML from the run page.
**๐ Why are some fields null for certain records?**
Some fields are optional at the source. The Actor returns `null` rather than fabricating values.
**๐ Can I run this on a schedule?**
Yes - use Apify's built-in scheduler or trigger via Make / Zapier / Webhooks.
**๐ฐ Is there a cost to use this Actor?**
Free users receive 10 records per run. [Create a paid account](https://console.apify.com/sign-up?fpr=vmoqkp) to unlock up to 1,000,000 records per run.
**๐ Does it cover european union (all parliamentary terms since 1979)?**
Yes - see the coverage line above the input section.
**๐ก๏ธ Is this Actor compliant?**
The Actor accesses only publicly available data, in line with the source's published terms of service.
### ๐ Integrate with any app
Export data directly from the Apify platform to:
**Spreadsheets & Databases**
Google Sheets - Microsoft Excel - Airtable - Notion - PostgreSQL - MySQL - MongoDB
**Automation & Workflows**
Make (Integromat) - Zapier - n8n - Pipedream - Activepieces
**Cloud Storage**
AWS S3 - Google Cloud Storage - Azure Blob Storage - Dropbox
**APIs & Webhooks**
REST API - Webhooks - Apify API
### ๐ Recommended Actors
| Actor | Description |
|---|---|
| [USPTO Patent Assignments Scraper](https://apify.com/parseforge/uspto-patent-assignments-scraper) | Extract USPTO patent ownership and assignment records |
| [FINRA BrokerCheck Scraper](https://apify.com/parseforge/finra-brokercheck-scraper) | Extract broker and firm registration data from FINRA's public database |
| [OurAirports Global Airport Database Scraper](https://apify.com/parseforge/ourairports-scraper) | Export worldwide airport data including ICAO/IATA codes |
> ๐ก **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge) for more public-data scrapers covering government records, legal filings, healthcare, finance, and more.
***
Need help? Visit the [Apify Discord community](https://discord.gg/jyEM2PRvMU) or open a support ticket.
**Disclaimer:** This Actor accesses publicly available data from European Parliament Open Data in compliance with the source's terms of service. Data is provided as-is for informational purposes. Verify all records against the official source before relying on them for legal or business decisions.
# Actor input Schema
## `maxItems` (type: `integer`):
Free users: 10. Paid users: optional, max 1,000,000.
## Actor input object example
```json
{
"maxItems": 10
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"maxItems": 10
};
// Run the Actor and wait for it to finish
const run = await client.actor("parseforge/european-mep-disclosures-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`๐พ 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);
});
// ๐ Want to learn more ๐? Go to โ 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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "maxItems": 10 }
# Run the Actor and wait for it to finish
run = client.actor("parseforge/european-mep-disclosures-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("๐พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"maxItems": 10
}' |
apify call parseforge/european-mep-disclosures-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=parseforge/european-mep-disclosures-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "European Parliament MEPs Scraper | MEP Profiles and Data",
"description": "Export Members of European Parliament records from the EU Open Data Portal: full name, identifier, given/family name, sort label and label. Combine with parliamentary terms for historical mapping. CSV, Excel, JSON or XML for political research and lobbying analysis.",
"version": "0.1",
"x-build-id": "UPATJv3Lrb2TsNwrD"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/parseforge~european-mep-disclosures-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-parseforge-european-mep-disclosures-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/parseforge~european-mep-disclosures-scraper/runs": {
"post": {
"operationId": "runs-sync-parseforge-european-mep-disclosures-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/parseforge~european-mep-disclosures-scraper/run-sync": {
"post": {
"operationId": "run-sync-parseforge-european-mep-disclosures-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"maxItems": {
"title": "Max Items",
"minimum": 1,
"maximum": 1000000,
"type": "integer",
"description": "Free users: 10. Paid users: optional, max 1,000,000."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```