> 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 by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.sportmonks.com/v3/sportmonks-ai-docs/mcp-server-beta/tools/search.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

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.
