# Scrape EU Tenders From TED

**Use case:** 

TED is the European Union's own publication office feed and it carries roughly 19,800 notices a week. The keyword is pushed into TED's full-text index, so notices that do not match are never downloaded and never charged for - which is a different thing from filtering them after the fact.

## Input

```json
{
  "sources": [
    "ted"
  ],
  "keyword": "software",
  "datePreset": "last_7_days",
  "excludeKeywords": [],
  "countries": [],
  "buyerNameContains": "Ministry of Defence",
  "cpvCodes": [],
  "noticeTypes": [],
  "contractNature": "",
  "stage": "any",
  "openOnly": false,
  "sortBy": "publication_date_desc",
  "outputLanguage": "eng",
  "maxItems": 1000,
  "maxItemsPerSource": 0,
  "includeDescription": true,
  "compactOutput": false,
  "dropEmptyFields": false,
  "includeRawSource": false,
  "incrementalMode": false,
  "emitUnchanged": false,
  "samMaxRowsScanned": 120000,
  "tedPageSize": 250
}
```

## Output

```json
{
  "title": {
    "label": "Title",
    "format": "string"
  },
  "buyer_name": {
    "label": "Buyer",
    "format": "string"
  },
  "buyer_country": {
    "label": "Buyer country",
    "format": "string"
  },
  "publication_date": {
    "label": "Published",
    "format": "string"
  },
  "deadline_date": {
    "label": "Deadline",
    "format": "string"
  },
  "days_to_deadline": {
    "label": "Days left",
    "format": "integer"
  },
  "is_open": {
    "label": "Still open",
    "format": "boolean"
  },
  "value_amount": {
    "label": "Value",
    "format": "integer"
  },
  "value_currency": {
    "label": "Currency",
    "format": "string"
  },
  "cpv_division_label": {
    "label": "Sector",
    "format": "string"
  },
  "notice_type_label": {
    "label": "Notice type name",
    "format": "string"
  },
  "notice_url": {
    "label": "Notice URL",
    "format": "string"
  },
  "source": {
    "label": "Source",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [Government Tenders Scraper - TED, SAM.gov, Procurement Data](https://apify.com/snow_leo_data/government-tenders-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/snow_leo_data/government-tenders-scraper.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/snow_leo_data/government-tenders-scraper.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).