> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cube.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# MCP Connectors

> Connect external MCP servers so the agent can use their tools — search Notion, file Linear issues, query Sentry, and more — from chat.

<Warning>
  MCP Connectors is currently in preview, and the user experience may still change.
  Reach out to the [Cube support team](/admin/account-billing/support) to activate this
  feature for your account.
</Warning>

MCP Connectors let the [agent](/admin/ai) use tools from external services. An
administrator connects an external [MCP](https://modelcontextprotocol.io) server — such as
Notion, Linear, Sentry, or Attio — and its tools become available to the agent in
[Analytics Chat](/docs/explore-analyze/analytics-chat). The agent can then search a Notion
workspace, file a Linear issue, look up a Sentry error, or call any tool a connected server
exposes, alongside the data it queries from your semantic model.

<Note>
  **MCP Connectors are the inverse of the [MCP server](/docs/integrations/mcp-server).** A
  connector lets the **Cube agent reach out** to an external MCP server and call its tools.
  The MCP server lets **external MCP clients reach in** to Cube and query your data. One is
  outbound, the other inbound — you can use either or both.
</Note>

## Concepts

* A **connector** is a connection to one external MCP server. Each connector is configured
  and authenticated once, at the organization level, by an administrator.
* Each connector exposes one or more **tools** — the individual actions the agent can call
  (for example, "search pages" or "create issue"). A single connector typically exposes
  many tools.
* Connectors are managed in the admin panel under **MCP Connectors** and apply across the
  organization, so every agent can use the tools you enable.

## Adding a connector

Open the admin panel and go to **MCP Connectors**. You can add a connector from the
built-in directory or connect a custom MCP server.

### From the directory

The connector directory includes vetted, first-party integrations with streamlined setup.

<Steps>
  <Step title="Browse the directory">
    Select **Browse directory** and choose a service (for example, Notion, Linear, Sentry,
    or Attio).
  </Step>

  <Step title="Authenticate">
    Complete the connector's authentication flow (see [Authentication](#authentication)
    below). For OAuth-based connectors you'll be redirected to the provider to authorize
    access.
  </Step>

  <Step title="Enable tools">
    Review the tools the connector exposes and choose which ones are available to the
    agent. See [Choosing which tools are available](#choosing-which-tools-are-available).
  </Step>
</Steps>

### Custom connector

Any service that exposes a remote MCP endpoint can be connected as a custom connector.

<Steps>
  <Step title="Add a custom connector">
    Select **Add custom connector** and provide a name and the server's HTTPS endpoint URL
    (for example, `https://mcp.example.com/mcp`).
  </Step>

  <Step title="Authenticate">
    Choose the authentication method the server requires — OAuth or a user-provided
    credential such as an API key or token.
  </Step>

  <Step title="Enable tools">
    Once connected, the server's tools are discovered automatically. Choose which ones the
    agent may call.
  </Step>
</Steps>

## Authentication

Connectors authenticate to the external service in one of two ways, depending on what the
service supports:

| Method                       | How it works                                                                                                                                                                   |
| ---------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **OAuth**                    | You authorize Cube with the provider through a standard OAuth flow. The connector stores the resulting tokens and refreshes them as needed. Used by most directory connectors. |
| **User-provided credential** | You supply a credential — such as an API key or access token — that the connector uses to authenticate. Used when a service does not offer OAuth.                              |

A connector's status indicator in the connectors list shows whether it is connected and
authenticated.

## Choosing which tools are available

Each connected server reports the full set of tools it exposes (shown as a count, for
example `16 / 16`). You control which of those tools the agent is allowed to call.
Enabling only the tools you need keeps the agent focused and limits what it can do through
each connector.

## How the agent uses connector tools

Once a connector is configured and its tools are enabled, the agent can call them in
[Analytics Chat](/docs/explore-analyze/analytics-chat) as part of answering a request — the
same way it queries your semantic model. The agent decides when a tool is relevant based on
the user's request and the tool's description. If a tool requires the user to authenticate
to the external service, the agent prompts for authorization in chat before the tool runs.

## Permissions

Managing MCP Connectors requires administrator access in Cube Cloud — the same access
needed to manage other organization-level settings in the admin panel. Connectors apply
across the organization; using the tools they expose is available to anyone with chat
access, subject to the tools you enable.

## Related

<CardGroup cols={2}>
  <Card title="MCP server" icon="plug" href="/docs/integrations/mcp-server">
    Let external MCP clients connect to Cube and query your data over HTTPS.
  </Card>

  <Card title="Overview" icon="robot" href="/admin/ai">
    Configure the agent that powers Cube's AI features.
  </Card>

  <Card title="Skills" icon="wand-magic-sparkles" href="/admin/ai/skills">
    Package reusable, named agent workflows users can run on demand from chat.
  </Card>

  <Card title="Analytics Chat" icon="comments" href="/docs/explore-analyze/analytics-chat">
    Ask questions of your data in natural language.
  </Card>
</CardGroup>
