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 CrewAI 8 tools — connect in under 2 minutes

Name: Confluence
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Confluence through the Vinkius — pass the Edge URL in the `mcps` parameter and every Confluence tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Confluence Specialist",
    goal="Help users interact with Confluence effectively",
    backstory=(
        "You are an expert at leveraging Confluence tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Confluence "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* 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.

When paired with CrewAI, Confluence becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Confluence tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Confluence MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 8 tools from Confluence

Why Use CrewAI with the Confluence MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Confluence through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Confluence + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Confluence for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Confluence, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Confluence tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Confluence against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Confluence MCP Tools for CrewAI (8)

These 8 tools become available when you connect Confluence to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Confluence + CrewAI FAQ

Common questions about integrating Confluence MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.