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For Developer

Follow the instructions below to integrate Confluence MCP server to your AI application using our API or SDK.

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Prerequisites

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1. Create a Confluence MCP Server

Use the following endpoint to create a new remote Confluence MCP server instance:

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Request

from klavis import Klavis
from klavis.types import McpServerName

klavis_client = Klavis(api_key="<YOUR_API_KEY>")

# Create a Confluence MCP server instance
confluence_server = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.CONFLUENCE,
    user_id="<YOUR_USER_ID>",
    platform_name="<YOUR_PLATFORM_NAME>",
)

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Response

{
  "serverUrl": "https://confluence-mcp-server.klavis.ai/mcp/?instance_id=<instance-id>",
  "instanceId": "<instance-id>",
  "oauthUrl": "https://api.klavis.ai/oauth/confluence/authorize?instance_id=<instance-id>"
}
serverUrl specifies the endpoint of the Confluence MCP server, which allows you to interact with Confluence spaces, pages, and content.
instanceId is used to get an authentication token. After you complete the OAuth flow, this token allows the MCP server to access Confluence on your behalf.

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2. Confluence OAuth Flow

Redirect users to the OAuth authorization flow: 
import webbrowser

webbrowser.open(confluence_server.oauth_url)

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Explore MCP Server Tools

For more details about tool input schema, use the list_tool API.