Confluence Cloud

Interact with Confluence Cloud to manage spaces, pages, and content.

Installation

Installing for Claude Desktop

Manual Configuration Required

This MCP server requires manual configuration. Run the command below to open your configuration file:

npx mcpbar@latest edit -c claude

This will open your configuration file where you can add the Confluence Cloud MCP server manually.

Confluence Cloud MCP Server

A Model Context Protocol (MCP) server that provides tools for interacting with Confluence Cloud. This server enables AI assistants to manage Confluence spaces, pages, and content through a standardized interface.

CI/CD Pipeline

Features

  • Space Management
    • List spaces
    • Get space details
  • Page Operations
    • Create, read, update pages
    • List pages in a space
    • Convert page content from Confluence storage format to Markdown
  • Search & Labels
    • Search content using CQL
    • Manage page labels

Setup

The easiest way to use this server is with the pre-built Docker image:

docker run --rm -i \
  -e CONFLUENCE_API_TOKEN=your-api-token \
  -e [email protected] \
  -e CONFLUENCE_DOMAIN=your-domain.atlassian.net \
  ghcr.io/aaronsb/confluence-cloud-mcp:latest

Option 2: Building Locally

  1. Clone the repository:
git clone https://github.com/aaronsb/confluence-cloud-mcp.git
cd confluence-cloud-mcp
  1. Build and run using the local build script:
# Build the Docker image
./scripts/build-local.sh

# Run the server
CONFLUENCE_API_TOKEN=your-token CONFLUENCE_EMAIL=your-email ./scripts/run-local.sh

Option 3: From Source

  1. Install dependencies:
npm install
  1. Configure environment variables: Create a .env file with your Confluence credentials:
CONFLUENCE_DOMAIN=your-domain.atlassian.net
[email protected]
CONFLUENCE_API_TOKEN=your-api-token
  1. Build the project:
npm run build
  1. Run the server:
node build/index.js

Usage

The server can be integrated with MCP-compatible AI assistants by adding it to their MCP configuration:

{
  "mcpServers": {
    "confluence": {
      "command": "docker",
      "args": ["run", "--rm", "-i", "ghcr.io/aaronsb/confluence-cloud-mcp:latest"],
      "env": {
        "CONFLUENCE_DOMAIN": "your-domain.atlassian.net",
        "CONFLUENCE_EMAIL": "[email protected]",
        "CONFLUENCE_API_TOKEN": "your-api-token"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

Note for AI Assistants: If you're an AI assistant like Cline trying to install this MCP server, please refer to the llms-install.md file for detailed installation instructions.

Available Tools

Space Tools

  • list_confluence_spaces: List all spaces in Confluence
  • get_confluence_space: Get details about a specific space

Page Tools

  • list_confluence_pages: List pages in a space
  • get_confluence_page: Get a specific page with its content (now includes Markdown conversion)
  • create_confluence_page: Create a new page in a space
  • update_confluence_page: Update an existing page

The get_confluence_page tool now automatically converts Confluence storage format content to Markdown, making it easier to work with page content. The conversion handles:

  • Headers (h1-h6)
  • Lists (ordered and unordered)
  • Links
  • Emphasis (bold/italic)
  • Code blocks
  • Tables
  • Paragraphs and line breaks

Search & Label Tools

  • search_confluence_pages: Search Confluence content using CQL
  • get_confluence_labels: Get labels for a page
  • add_confluence_label: Add a label to a page
  • remove_confluence_label: Remove a label from a page

Note: All tool names follow the [verb]confluence[noun] naming convention for consistency and clarity.

Development

This project is written in TypeScript and follows the MCP SDK conventions for implementing server capabilities. The codebase is organized into:

  • src/client/ - Confluence API client implementation
  • src/handlers/ - MCP tool request handlers
  • src/schemas/ - JSON schemas for tool inputs
  • src/types/ - TypeScript type definitions
  • src/utils/ - Utility functions including content format conversion

CI/CD Pipeline

This project uses GitHub Actions for continuous integration and deployment:

  • Automated testing and linting on pull requests
  • Automatic Docker image builds on main branch commits
  • Multi-architecture image builds (amd64, arm64)
  • Container publishing to GitHub Container Registry

Local Development

For local development, use the provided scripts:

  • ./scripts/build-local.sh: Builds the project and creates a local Docker image
  • ./scripts/run-local.sh: Runs the local Docker image with your credentials

License

MIT

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Confluence Cloud: MCP Server – MCP.Bar