How do I generate an Atlassian API Token?

Log into your Atlassian account at id.atlassian.com, navigate to the **Security** tab, and click on **API tokens**. Select 'Create and manage API tokens' to generate a new key for this integration.

Can the AI edit all spaces within my Confluence account?

The AI integration adheres strictly to the permissions of the user generating the API token. It can only read and modify the spaces that your specific Atlassian user account has authorization to access.

Does a published Confluence page support Markdown?

Yes, Confluence correctly processes standard formatting such as headings, lists, code blocks, and rich text when the AI agent generates and uploads content.

Confluence MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Confluence
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Confluence through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Confluence "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Confluence?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Confluence MCP Server

Connect your Atlassian Confluence workspace to your AI assistant. Easily query your organization's knowledge base, search through technical documentation, and seamlessly generate new formatted pages right from the conversational interface.

Pydantic AI validates every Confluence tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Search Wiki Spaces — Quickly retrieve specific software architecture decisions, HR policies, or meeting notes without switching tabs.
Read Pages — Extract the complete text and markdown-structured content of existing wiki pages for quick summaries.
Create & Publish — Draft robust product requirements documents (PRDs) or meeting minutes using the AI, and publish them directly to your designated Confluence spaces.

The Confluence MCP Server exposes 8 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Confluence to Pydantic AI via MCP

Follow these steps to integrate the Confluence MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 8 tools from Confluence with type-safe schemas

Why Use Pydantic AI with the Confluence MCP Server

Pydantic AI provides unique advantages when paired with Confluence through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Confluence integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Confluence connection logic from agent behavior for testable, maintainable code

Confluence + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Confluence MCP Server delivers measurable value.

Type-safe data pipelines: query Confluence with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Confluence tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Confluence and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Confluence responses and write comprehensive agent tests

Confluence MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Confluence to Pydantic AI via MCP:

add_page_comment

The body should be in storage format (HTML). Add a new comment to a Confluence page

create_page

Requires the space key, a title, and body content in Confluence storage format (HTML). The page is created at the root of the space. Create a new page in a Confluence space

get_page

Returns content body, space, version history, and metadata. Retrieve detailed information about a specific page

get_space_details

Returns metadata, description, homepage, and permissions overview. Retrieve detailed information about a specific space

list_page_comments

Returns inline and footer comments with author and content. Retrieve all comments for a specific Confluence page

list_pages

Optionally filter by space key. Supports pagination via start offset and limit. Retrieve a list of pages from Confluence

list_spaces

Retrieve a list of all spaces in Confluence

search_confluence

g. text ~ "project" AND type = "page"). Returns matching pages, blog posts, and comments. Search for content using Confluence Query Language (CQL)

Example Prompts for Confluence in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Confluence immediately.

"Search Confluence for documentation regarding our 'Q3 Migration Plan'."

"Create a new page in the 'Product' space summarizing our meeting notes from today."

"List all wiki pages currently under the space key 'HR'."

Troubleshooting Confluence MCP Server with Pydantic AI

Common issues when connecting Confluence to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Confluence + Pydantic AI FAQ

Common questions about integrating Confluence MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your Confluence MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.