How to Use the Confluence MCP in Pydantic AI

Q: Can I use Pydantic AI to comment on Confluence pages?

Yes, you use the addpagecomment tool. You just need to provide the page ID and the comment body in HTML storage format.

Q: How do I list comments in Pydantic AI from Confluence?

Call listpagecomments with the page ID. You will get a structured list of authors and message bodies for your agent to process.

Use Pydantic AI for type-safe Confluence interactions with runtime validation for every page action.

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Connect Confluence MCP to Pydantic AI

Create your Vinkius account to connect Confluence to Pydantic AI 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 Pydantic AI

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Type-safe page management in Pydantic AI

Every response from `get_page` is validated against your Pydantic schemas. If the API returns malformed data, your agent stops immediately before a crash occurs. Use `create_page` to push new content confidently. The tool signature ensures your HTML body and space keys are formatted correctly every time.

Search and discover with Pydantic AI

Run `search_confluence` to find specific pages using complex queries. Your agent receives structured output that maps directly to your models. `list_pages` provides a reliable list of documents. You can filter by space key to keep your agent's scope manageable and precise.

Workspace intelligence for Pydantic AI

Retrieve detailed metadata with `get_space_details` to understand permissions and homepage structure. It helps your agent make informed decisions about where to post updates. Use `list_spaces` to get a clean list of your available environments. This MCP server ensures your agent always interacts with the right space.

Setup guide

Set up Confluence MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "confluence-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Confluence tools.",
)

result = await agent.run("List recent Confluence transactions")
print(result.output)

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Common questions about Confluence MCP in Pydantic AI

The library checks every tool response against your defined models. If the Confluence API returns unexpected fields, your agent raises a clear validation error.

Yes, you use the `add_page_comment` tool. You just need to provide the page ID and the comment body in HTML storage format.

Call `list_page_comments` with the page ID. You will get a structured list of authors and message bodies for your agent to process.

Yes, all data travels through an encrypted tunnel. Your endpoint token acts as the only key, keeping your wiki access isolated.

We process your Confluence page text in memory only. No content is stored, logged, or analyzed by our servers, keeping your company data private.

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