# External Search

External search can query your custom search API and the response from the API can return contact information that will be shown in the search panel. A simple execution of this can be created by using Microsoft Flow.

External Search will send a HTTP POST to the specified URL. A JSON object with specific properties is sent in the body. The response body JSON array object(s) are expected to have specific property names.

#### Example HTTP POST Body:

Only populated properties will be sent in the body.

```
{
  "searchTerm": "John Doe",
  "departments": [
    "Sales"
  ],
  "officeLocations": [
    "New York"
  ],
  "countries": [
    "USA"
  ],
  "jobTitles": [
    "Sales Manager"
  ],
  "postalCodes": [
    "10002"
  ],
  "givenName": [
    "John"
  ],
  "surname": [
    "Doe"
  ],
  "displayNames": [
    "John Doe"
  ],
  "mail": [
    "jdoe@contoso.com"
  ],
  "userPrincipalName": [
    "jdoe@contoso.com"
  ],
  "maxContactSearchResults": "20"
}
```

#### Example HTTP Response Body:

All properties are optional and the values can be null. 

Properties are case sensitive. 

Properties that are not expected will be ignored.

```
[
    {
        "azureAdId": null,
        "givenName": "John",
        "surname": "doe",
        "displayName": "John doe",
        "userPricipalName": "jdoe@contoso.com",
        "companyName": "Contoso",
        "jobTitle": "Sales Manager",
        "department": "Sales",
        "officeLocation": "New York",
        "emailAddress": "jdoe@contoso.com",
        "businessPhone": "810-653-3163",
        "mobilePhone": "810-653-3163",
        "preferredLanguage": null,
        "notes": null,
        "country": "USA"
    }
]
```


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# Agent Instructions: 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:

```
GET https://ac.docs.landis.cloud/appendix/external-search.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.