How to Use the Confluence MCP in Google ADK

Q: How can I search Confluence content via Google ADK?

You use the searchconfluence tool, which supports CQL. Your agent sends the query string and receives a list of relevant pages or blog posts.

Q: Does Google ADK support writing to Confluence?

Yes, the createpage and addpagecomment tools allow your agent to modify your wiki directly. Ensure your token has the correct write permissions.

Q: Can Google ADK read large Confluence spaces?

Yes, by using pagination in listpages. You can iterate through your entire wiki without hitting request limits.

Connect your Confluence workspace to Google ADK to build agents that act on your team's internal knowledge.

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Connect Confluence MCP to Google ADK

Create your Vinkius account to connect Confluence to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Confluence with Google ADK

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Google ADK agents interacting with Confluence

Your agents can now fetch page data with `get_page` to feed into your Gemini model's context. This works perfectly for summarizing long docs stored in your company wiki. Use `list_page_comments` to pull discussion threads. It gives your agent a complete view of the conversation history on any specific page.

Programmatic page creation in Google ADK

Automate your reporting by using `create_page` to generate new documentation from your agent's findings. You just provide the space key and the HTML content. `list_pages` allows your agent to scan existing docs before creating new ones. This helps avoid duplicate content in your workspace.

Space metadata access for Google ADK

Get a clear picture of your workspace structure using `get_space_details`. Your agent reads the homepage and permissions to decide if it has access to modify content. Use `list_spaces` to inventory all available projects. This ensures your agent always targets the correct space for its operations.

Setup guide

Set up Confluence MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Confluence tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Confluence_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Confluence tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Confluence MCP in Google ADK

You use the `search_confluence` tool, which supports CQL. Your agent sends the query string and receives a list of relevant pages or blog posts.

Yes, the `create_page` and `add_page_comment` tools allow your agent to modify your wiki directly. Ensure your token has the correct write permissions.

Yes, by using pagination in `list_pages`. You can iterate through your entire wiki without hitting request limits.

No, you only provide a single endpoint token to the server. Your actual login credentials remain private and are never exposed.

Page text is transmitted as raw HTML via the MCP protocol. No data is cached by our infrastructure, ensuring your wiki remains secure.

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