How to Build a Confluence MCP Server (AI Access to Your Wiki)

Why Connect Confluence to AI?

Confluence stores team knowledge: documentation, meeting notes, specs, runbooks, and decision records. AI agents with Confluence access become knowledge assistants that can search pages, pull relevant docs into context, create new pages, and keep documentation up to date.

Confluence's REST API requires Atlassian API tokens, space keys, and content IDs. The API uses a custom storage format (Atlassian Document Format) that differs from what you see in the editor. Building a proper integration means understanding their content model, handling pagination, and managing the ADF markup.

DataFaucet skips all of that.

How It Works

1. Go to DataFaucet and enter your Confluence URL
2. Log into your Confluence instance in the cloud browser
3. Browse spaces, search pages, create content, add comments
4. Every API call gets captured automatically
5. Select which actions become tools, click deploy

You get a hosted MCP server with tools like search_pages, get_page_content, create_page, add_comment ready for any MCP client.

What Gets Captured

DataFaucet watches real Confluence API traffic as you interact:

• Pages — search, get content, create, update, archive
• Spaces — list, get pages, get blog posts
• Comments — add inline or page-level comments
• Attachments — list, upload, download
• Labels — add, remove, search by label
• Search — CQL queries across all content
• Templates — list available templates, create from template
• Page tree — get child pages, navigate hierarchy

Each becomes a typed MCP tool with parameters inferred from actual requests.

Example Tools Generated

search_pages        — Search across all Confluence content (CQL)
get_page_content    — Get full page content by ID or title
create_page         — Create a new page in a space
update_page         — Update existing page content
add_comment         — Add a comment to a page
get_space_pages     — List all pages in a space
get_child_pages     — Get child pages of a parent page

Use Cases

• Knowledge retrieval — AI searches Confluence for relevant docs when answering questions
• Documentation updates — AI creates or updates pages when specs change
• Onboarding assistance — AI pulls relevant runbooks and guides for new team members
• Meeting notes — AI creates structured meeting pages from transcripts
• Decision tracking — AI searches for related ADRs and past decisions before recommending approaches
• Code documentation — Cursor pulls Confluence specs while writing implementation

Connect to Your AI Client

{
  "mcpServers": {
    "confluence": {
      "url": "https://datafaucet.dev/api/mcp/YOUR_SERVER_ID/sse"
    }
  }
}

Works with Claude Desktop, Cursor, Windsurf, Codex, and any MCP-compatible client.

Why Not Use Confluence's API Directly?

Confluence content uses Atlassian Document Format (ADF), a complex JSON structure that doesn't map to what you see in the editor. Creating or updating pages requires constructing valid ADF nodes. DataFaucet captures the exact API calls your browser makes, including the correct ADF structure, so you never need to construct it manually.

Get Started

Create your Confluence MCP server in 60 seconds. Free tier includes 3 servers, no credit card required.

Related: Jira MCP Server for Atlassian issue tracking, Notion MCP Server for Notion workspaces, Google Sheets MCP Server for spreadsheet access.