> For the complete documentation index, see [llms.txt](https://university.mindstudio.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://university.mindstudio.ai/building-ai-agents/blocks-reference/find-contact-email-for-website.md).

# Find Contact Email for Website

## Configuration 

### Domain

Enter the domain for the company whose emails you want to search for. This section can include variables. 

### Output 

Save the returned data as a variable. Example: `Contact_Emails`

## Sample Output

```json

  "data": {
    "domain": "intercom.com",
    "disposable": false,
    "webmail": false,
    "accept_all": true,
    "pattern": "{first}",
    "organization": "Intercom",
    "description": "Faster resolutions, higher CSAT, and lighter support volumes with the only platform to combine the power of automation and human customer support.",
    "industry": "Software Development",
    "twitter": null,
    "facebook": null,
    "linkedin": null,
    "instagram": null,
    "youtube": null,
    "technologies": ["amazon-web-services", "facebook", "intercom", "marketo", "node-js", "react", "recaptcha", "sentry"],
    "country": null,
    "state": null,
    "city": null,
    "postal_code": null,
    "street": null,
    "headcount": "501-1000",
    "company_type": "Educational Institution",
    "emails": [
      {
        "value": "ciaran@intercom.com",
        "type": "personal",
        "confidence": 92,
        "sources": [
          {
            "domain": "github.com",
            "uri": "http://github.com/ciaranlee",
            "extracted_on": "2015-07-29",
            "last_seen_on": "2017-07-01",
            "still_on_page": true
          },
          {
            "domain": "blog.intercom.com",
            "uri": "http://blog.intercom.com/were-hiring-a-support-engineer/",
            "extracted_on": "2015-08-29",
            "last_seen_on": "2017-07-01",
            "still_on_page": true
          },
          ...
        ],
        "first_name": "Ciaran",
        "last_name": "Lee",
        "position": "Support Engineer",
        "position_raw": "Support Engineer",
        "seniority": "senior",
        "department": "it",
        "linkedin": null,
        "twitter": "ciaran_lee",
        "phone_number": null,
        "verification": {
          "date": "2019-12-06",
          "status": "valid"
        }
      },
      ...
    ],
    "linked_domains": []
  },
  "meta": {
    "results": 35,
    "limit": 10,
    "offset": 0,
    "params": {
      "domain": "intercom.com",
      "company": null,
      "type": null,
      "seniority": null,
      "department": null
    }
  }
}
```


---

# Agent Instructions
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## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://university.mindstudio.ai/building-ai-agents/blocks-reference/find-contact-email-for-website.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.