> For the complete documentation index, see [llms.txt](https://docs.sportmonks.com/v3/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sportmonks.com/v3/sportmonks-ai-docs/mcp-server-beta/tools/search.md).

# Search

The `search` tool is usually the right starting point. Use it to find the ID of a player, team, or league before calling other tools.

### Tool

| Tool     | Description                                                 |
| -------- | ----------------------------------------------------------- |
| `search` | Search players, teams, leagues, or all entity types by name |

### Parameters

| Parameter | Type   | Required | Description                                                                    |
| --------- | ------ | -------- | ------------------------------------------------------------------------------ |
| `query`   | string | Yes      | Name or partial name to search for                                             |
| `type`    | string | No       | Entity type to search: `player`, `team`, `league`, or `all`. Defaults to `all` |

### Response

Returns up to 25 results sorted alphabetically. Each result includes:

```json
{
  "id": 123,
  "entity_type": "team",
  "name": "Arsenal",
  "country": "England"
}
```

The `country` field helps disambiguate results where many entities share the same name (e.g. multiple leagues named "Super League" across different countries).

### Example prompts

* *Search for "Arsenal"*
* *Search for players named "Silva"*
* *Find the league ID for the Premier League*
* *Search for "Haaland" - player only*


---

# 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:

```
GET https://docs.sportmonks.com/v3/sportmonks-ai-docs/mcp-server-beta/tools/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.