Connect agents to external services

Important

This feature is in Public Preview.

Connect your AI agents to external applications like Slack, Google Calendar, or any service with an API. Azure Databricks provides several approaches depending on whether the external service has an MCP server, whether you need per-user authentication, or whether you prefer to call APIs directly from agent code. All approaches rely on a Unity Catalog HTTP connection to securely manage credentials and govern access to external services.

Approach	Recommended use case
External MCP servers	Use this approach for services that publish an MCP server. It provides automatic tool discovery and works with standard SDKs.
Managed OAuth	Use this approach for Google Drive or SharePoint integrations. Azure Databricks manages the OAuth credentials, so no app registration is required.
UC connections proxy	Use this approach to make direct REST API calls from agent code using the external service's own client SDK.
UC function tools	Use this approach for SQL-based tool definitions that wrap the http_request() function.

Requirements

• A Unity Catalog HTTP connection for your external application. Unity Catalog connections provide secure, governed credential management and enable multiple authentication methods, including OAuth 2.0 user-to-machine and machine-to-machine authentication.

External MCP servers

If the external service has an MCP server available, Azure Databricks recommends connecting through external MCP servers. MCP servers provide automatic tool discovery, simplified integration, and per-user authentication.

• See Install an external MCP server for installation and authentication setup.
• See Use external MCP servers in agents for code examples per agent framework (OpenAI Agents SDK, LangGraph, Model Serving).

Managed OAuth

Azure Databricks offers managed OAuth flows for select API tool providers. You don't need to register your own OAuth app or manage credentials. Azure Databricks recommends Managed OAuth for development and testing. If production use cases require generating custom OAuth credentials, see the providers' documentation for more information.

The following integrations use Azure Databricks-managed OAuth credentials stored securely in the backend.

Provider	Configuration notes	Supported scopes	Description
Google Drive API	None	https://www.googleapis.com/auth/drive.readonly https://www.googleapis.com/auth/documents.readonly https://www.googleapis.com/auth/spreadsheets.readonly offline_access	Read-only access to Google Drive files.
SharePoint API	None	https://graph.microsoft.com/Sites.Read.All offline_access openid profile	Read-only access to SharePoint sites.

To set up managed OAuth, create an HTTP connection with the OAuth User to Machine Per User auth type and select your provider from the OAuth Provider drop-down menu. For detailed steps, see Installation methods.

Each user is prompted to authorize with the provider on first use.

If needed, allowlist the following redirect URIs used by managed OAuth:

Cloud	Redirect URI
AWS	https://oregon.cloud.databricks.com/api/2.0/http/oauth/redirect
Azure	https://westus.azuredatabricks.net/api/2.0/http/oauth/redirect
GCP	https://us-central1.gcp.databricks.com/api/2.0/http/oauth/redirect

UC connections proxy endpoint

Use the Unity Catalog connections proxy endpoint with the external service's own client SDK to call REST APIs directly from agent code. Point the SDK's base URL to the proxy endpoint and use your Azure Databricks token as the API key. Azure Databricks authenticates the request and automatically injects the external service's credentials from the Unity Catalog connection. Your code never handles the external service's tokens directly.

Permissions required: USE CONNECTION on the connection object.

OpenAI

Use DatabricksOpenAI to route calls to external OpenAI through the Unity Catalog connections proxy. First, create a Unity Catalog HTTP connection using your OpenAI API key stored as a Databricks secret:

CREATE CONNECTION openai_connection TYPE HTTP
OPTIONS (
  host 'https://api.openai.com',
  base_path '/v1',
  bearer_token secret ('<secret-scope>', '<secret-key>')
);

Then install the databricks-openai package and use the proxy URL and workspace client in your agent code:

pip install databricks-openai

from databricks_openai import DatabricksOpenAI
from databricks.sdk import WorkspaceClient

w = WorkspaceClient()

client = DatabricksOpenAI(
    workspace_client=w,
    base_url=f"{w.config.host}/api/2.0/unity-catalog/connections/openai_connection/proxy/",
)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

Slack

Configure the Slack SDK to route through the Unity Catalog connections proxy. Create a Unity Catalog HTTP connection with host https://slack.com and base path /api, then use the proxy URL as the SDK base URL:

from slack_sdk import WebClient
from databricks.sdk import WorkspaceClient

w = WorkspaceClient()

client = WebClient(
    token=w.config.authenticate()["Authorization"].split(" ")[1],
    base_url=f"{w.config.host}/api/2.0/unity-catalog/connections/slack_connection/proxy/",
)

result = client.chat_postMessage(channel="C123456", text="Hello from Databricks!")
print(result["message"]["text"])

Generic HTTP

For services without a dedicated SDK, use the requests library with the proxy URL directly:

import requests
from databricks.sdk import WorkspaceClient

w = WorkspaceClient()

response = requests.post(
    f"{w.config.host}/api/2.0/unity-catalog/connections/my_connection/proxy/api/v1/resource",
    headers={
        **w.config.authenticate(),
        "Content-Type": "application/json",
    },
    json={"key": "value"},
)

UC function tools with HTTP connections

Note

Azure Databricks recommends using MCP servers or the UC connections proxy for new integrations. UC function tools with http_request remain supported but are no longer the recommended approach.

You can create a Unity Catalog function that wraps http_request() to call external services. This approach is useful for SQL-based tool definitions. See Create AI agent tools using Unity Catalog functions for details on creating UC function tools.

The following example creates a Unity Catalog function tool that posts a message to Slack:

CREATE OR REPLACE FUNCTION main.default.slack_post_message(
  text STRING COMMENT 'message content'
)
RETURNS STRING
COMMENT 'Sends a Slack message by passing in the message and returns the response received from the external service.'
RETURN (http_request(
  conn => 'test_sql_slack',
  method => 'POST',
  path => '/api/chat.postMessage',
  json => to_json(named_struct(
    'channel', "C032G2DAH3",
    'text', text
  ))
)).text

See CREATE FUNCTION (SQL and Python).

Note

SQL access with http_request is blocked for the User-to-Machine Per User and Dynamic Client Registration connection types. Use the Python Azure Databricks SDK instead.

Example notebooks

Connect an agent to Slack

See Connect an AI agent to Slack.

Connect an agent to Microsoft Teams

See Connect an AI agent to Microsoft Teams.

External connection tools

The following notebooks demonstrate creating AI agent tools that connect to Slack, OpenAI, and Azure AI search.

Slack messaging agent tool

Get notebook

Microsoft Graph API agent tool

Get notebook

Azure AI Search agent tool

Get notebook