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How to Use the Confluence MCP in AutoGen

Let AutoGen agents debate, edit, and publish Confluence pages through collaborative workflows.

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Connect Confluence MCP to AutoGen

Create your Vinkius account to connect Confluence to AutoGen 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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Collaborative page creation with AutoGen

`create_page` allows your writing agent to publish draft pages directly to a specific space. Meanwhile, a separate editing agent can review the content and suggest changes before final publication. This MCP Server setup enables a consensus-driven workflow where agents debate the structure of the HTML body. They only commit the page to the root space once they agree on the layout.

Drive discussion threads via agent debate

`add_page_comment` lets a reviewer agent post feedback directly onto a page in HTML storage format. This mimics human collaboration, letting agents resolve conflicts in the comment section. By using `list_page_comments`, a supervisor agent can read existing inline feedback to decide if a page needs revision. This automates the editorial review process without human intervention.

Map out wiki architecture automatically

`list_spaces` gives your discovery agent a starting point by listing all active directories. It then coordinates with other agents to explore specific pages using `list_pages` to map out the wiki structure. When the team needs specific information, `search_confluence` executes CQL queries to find matching blog posts and comments. The agents then debate which source is the most reliable before presenting it.

Setup guide

Set up Confluence MCP in AutoGen

Prerequisites

  • Python 3.10+ installed
  • autogen-ext[mcp] package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install AutoGen with MCP

    Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.

  2. 2

    Fetch tools from the MCP

    Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

  3. 3

    Run your agent

    Pass the tools to AssistantAgent and call agent.run(). The agent invokes Confluence tools and returns structured results.

agent.py
from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Confluence_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Confluence data")
print(result.messages[-1].content)

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Common questions about Confluence MCP in AutoGen

You register the tools with the AutoGen `AssistantAgent` constructor. This lets all agents in your conversation group call tools like `get_page` when they need wiki data.
Yes. You can assign the `create_page` tool to a writer agent and the `list_page_comments` tool to a reviewer agent to build an automated editorial pipeline.
If `search_confluence` returns an error due to invalid CQL, the calling AutoGen agent can analyze the error message, debate the syntax with other agents, and try a corrected query.
Use the `StreamableHttpServerParams` helper from the AutoGen MCP extension. Point it to your Vinkius server URL, and the adapter will automatically handle the tool schema conversion.
Yes. The Confluence MCP Server on Vinkius runs in an ephemeral environment, meaning your HTML page body content and comments are processed in memory and never stored on our servers.

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