Confluence MCP. Search your knowledge base without switching tabs.
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Confluence MCP connects your AI agent directly to your organization’s knowledge base. Query technical documentation, find HR policies, and manage team resources by searching through wiki spaces using natural language prompts.
It lets you pull structured data from existing pages or draft new content—like product requirement documents—and publish them without ever leaving your chat window.
What your AI agents can do
Add label
Adds an organizational label to any existing wiki page for easier filtering later on.
Add page comment
Allows you to post a new comment body, formatted in HTML, onto a specific Confluence page.
Create page
Generates and publishes an entirely new wiki page into a specified space, requiring a title and content body.
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Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Confluence: 12 Knowledge Tools
Use these twelve tools to perform every CRUD action on your wiki, from listing all available spaces to deleting old pages.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Confluence on Vinkius019e9aa4add label
Adds an organizational label to any existing wiki page for easier filtering later on.
019d7579add page comment
Allows you to post a new comment body, formatted in HTML, onto a specific Confluence page.
019d7579create page
Generates and publishes an entirely new wiki page into a specified space, requiring a title and content body.
019e9aa4delete page
Permanently removes a Confluence page. Be aware this action cannot be undone.
019d7579get page
Fetches the full text, metadata, and version history for one specific wiki page.
019e9aa4get page history
Retrieves a timeline of every change made to a Confluence page, showing who did it and when.
019d7579get space details
Pulls metadata on an entire wiki space, including its description, homepage link, and permission structure.
019e9aa4list labels
Lists all labels currently applied to a specific Confluence page.
019d7579list page comments
Gathers every inline and footer comment from a page, including the author's name and the content of the message.
019d7579list pages
Retrieves a paginated list of all pages within a space, optionally filtering by key.
019d7579list spaces
Outputs a full inventory of every available wiki space in the organization's Confluence instance.
019d7579search confluence
Searches for content across the entire wiki using complex queries targeting pages, blog posts, and comments.
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Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Confluence. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 12 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
The Knowledge Silo Problem
Right now, finding reliable information means clicking through pages of links. You open the main Confluence page, then click into sub-spaces, and if you need a policy from HR that was mentioned in an old Engineering meeting, you're forced to manually cross-reference multiple sections—it’s slow and error-prone.
With this MCP, your agent handles all that clicking. You simply ask the question in chat, and it runs advanced searches across every relevant space and document type. You get a single, sourced answer right away.
Structured Publishing with `create_page`
Before this MCP, if you wrote a draft PRD in your chat window, the process was: copy text, open Confluence, navigate to the right space, click 'New Page', paste content. It’s four separate manual steps.
Now, you just tell your agent to create the page. The entire document—formatted and published with a single command—is live in the target wiki space.
What you can do with this MCP connector
Think of this MCP as a direct line into your company’s entire internal knowledge base. You stop clicking tabs and start asking questions. Instead of manually navigating through different wiki spaces to find an HR policy or an old architecture decision, you just ask your AI client. It searches every relevant space, giving you the exact text snippet you need right away.
Need to update documentation? Draft a new product requirement document (PRD) in chat, and then publish it directly into the correct Confluence space. You can also retrieve full pages or check who last edited something with granular detail. The real value shows up when your agent pulls knowledge from this MCP and chains that data with an external billing system MCP to automatically generate a project status report.
This whole process happens securely, because Vinkius manages all credential flow through a zero-trust proxy, meaning your keys never sit on disk.
It's about getting instant answers and making sure the documentation stays current—all without ever needing to log into Confluence itself.
019d7579-fb21-7008-b501-bfdb296f7e6f 
How Confluence MCP Works
- 1 First, authorize this MCP using your Atlassian API token. This grants your AI agent permission to interact with the wiki spaces.
- 2 Next, tell your agent exactly what you're looking for—for example, 'What was the decision on Project X?' The MCP executes a structured search against all connected spaces.
- 3 Finally, your agent returns the matching page content or metadata. You get the information presented back in plain text within your chat interface.
The bottom line is you use natural conversation to perform complex, multi-step administrative tasks on your corporate wiki.
Who Is Confluence MCP For?
Product Managers who are tired of copying and pasting meeting notes into Confluence; Technical Writers needing instant access to policy details; Engineers who waste time searching through archived technical guides.
Uses the MCP to search for specific architectural decisions across multiple spaces, gathering reference material before drafting a new guide.
Drafts PRDs in chat and uses the create_page tool to publish them directly into the designated Product Space when planning sessions wrap up.
Retrieves specific company policies, like 'PTO accrual rules', by running a targeted search against the HR space key in a conversational thread.
What Changes When You Connect
- Need to find a policy? Use
search_confluenceto query every piece of documentation, finding answers across spaces instead of relying on keyword matching in one area. - Drafting new content is faster than ever. After writing meeting minutes or PRDs, use
create_pageand publish them directly into the right space from your chat. - Never lose context again. If you need to know who changed a document and when, run
get_page_historyfor a full audit trail of changes. - Understand your entire wiki structure with
list_spaces. This helps map out which teams own which knowledge areas before starting a project. - The agent can pull detailed page content using
get_page, giving you not just the text, but also space metadata and version information all at once.
Real-World Use Cases
Finding an old design spec
A developer needs to know the original API contract for a service. Instead of asking three people which wiki space it's in, they run search_confluence and immediately pull up the specific technical guideline document.
Onboarding new hires
The HR manager wants to give a new employee a full overview of company policies. They use list_pages on the 'HR' space key, getting a list of all relevant documents like 'Leave Policies' and 'Benefits', which they can then share.
Project Retrospective
The team needs to write up lessons learned from a past project. They use get_page on the final post-mortem document, gathering not just content but also metadata and version history for accuracy.
Cleaning up old data
A Product Manager notices several outdated drafts in a specific space. They can list all pages using list_pages and then use delete_page on the confirmed obsolete content, keeping the knowledge base clean.
The Tradeoffs
Manual copy-pasting of notes
A user writes a summary in their chat and then has to manually open Confluence, find the 'Product' space, click 'Create', and paste everything.
→
Just run your agent with create_page. You give it the title and content, and it handles the formatting and publishing steps automatically.
Searching only by keywords
A user types 'migration plan' into a basic search bar but misses related blog posts or comments because the tool scope is too narrow.
→
Use search_confluence. This command uses Confluence Query Language to check pages, blog posts, and comments for comprehensive results.
Forgetting where content lives
The team knows the policy exists but doesn't know if it's in 'HR', 'Engineering', or 'Operations'. They waste time asking multiple people.
→
Start by calling list_spaces to map out all available areas. Then, drill down into specific spaces using list_pages for better focus.
When It Fits, When It Doesn't
Use this MCP if your core problem is internal documentation: you need to read, write, or manage content that lives in Confluence. You should use it when you need the full lifecycle—from drafting a concept (using create_page) to finding an obscure policy (using search_confluence). Don't use this if your goal is simply messaging; don't try to send a Slack notification with it. If you just need to list all users, that's an identity management MCP job. The strength here is the ability to chain knowledge: combine get_page data with a ticketing system MCP to automatically generate incident reports.
Common Questions About Confluence MCP
How do I search for documentation using `search_confluence`? +
You use natural language to prompt your agent. For instance, 'Search Confluence for all documents about Q3 budget cuts.' The tool handles translating that into a complex query across the entire wiki.
Can I find out who wrote which page using `get_page`? +
Yes. When you run get_page, it returns detailed metadata, including version history and authorship information, so you know exactly where the content came from.
What is the difference between `list_pages` and `search_confluence`? +
list_pages gives you a list of contents within one space. search_confluence actually looks inside the content, finding matches across many spaces.
Do I need to use `add_label` every time I create a page? +
No. You can call create_page first and then run add_label later if you decide the content needs further categorization or filtering.
How do I find out what spaces exist before I can use `list_pages`? +
You first use list_spaces to get a directory of all available Confluence areas. This tool returns a list of space keys and metadata, letting you know exactly which spaces your agent can interact with next.
Should I use `get_page_history` before using `delete_page`? +
Yes, always check the history first. The get_page_history tool retrieves every version change and timestamp for a page, giving you an irreversible audit trail of who changed what and when.
What is the best way to review comments on a specific page using `list_page_comments`? +
You run list_page_comments and provide the target page key. It returns all inline and footer comments, including the author's name and the full content of their input.
Does `create_page` require me to know the exact format for the body content? +
Yes, when running create_page, you must provide the title, space key, and the body content formatted in Confluence storage (HTML) format. The tool cannot guess formatting.
Multi-server workflows that include Confluence MCP
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Pipeline fails tracked, documentation cross-checked, team notified , engineering visibility without status meetings
MCP Workflow to Sync Sprint Knowledge
Your sprint ended, 14 tickets are done, and the PM is asking 'so what shipped?' , because nobody updated the Confluence release page since February
Turn Support Tickets Into KB Articles via MCP
Your support team answered 'how to reset my password' 340 times this quarter , each time a $65/hour agent spent 8 minutes writing the same answer because nobody turned the first answer into a knowledge base article
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