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    Confluence Cloud Mcp

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

    15 stars
    TypeScript
    Updated Jul 31, 2025

    Table of Contents

    • Features
    • Setup
    • Option 1: Using Docker (Recommended)
    • Option 2: Building Locally
    • Option 3: Using npx (Direct from GitHub)
    • Option 4: From Source
    • Usage
    • Available Tools
    • Space Tools
    • Page Tools
    • Search & Label Tools
    • Development
    • CI/CD Pipeline
    • Local Development
    • License

    Table of Contents

    • Features
    • Setup
    • Option 1: Using Docker (Recommended)
    • Option 2: Building Locally
    • Option 3: Using npx (Direct from GitHub)
    • Option 4: From Source
    • Usage
    • Available Tools
    • Space Tools
    • Page Tools
    • Search & Label Tools
    • Development
    • CI/CD Pipeline
    • Local Development
    • License

    Documentation

    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

    Option 1: Using Docker (Recommended)

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

    bash
    docker run --rm -i \
      -e CONFLUENCE_API_TOKEN=your-api-token \
      -e CONFLUENCE_EMAIL=your-email@domain.com \
      -e CONFLUENCE_DOMAIN=your-domain.atlassian.net \
      ghcr.io/aaronsb/confluence-cloud-mcp:latest

    Option 2: Building Locally

    1. Clone the repository:

    bash
    git clone https://github.com/aaronsb/confluence-cloud-mcp.git
    cd confluence-cloud-mcp

    2. Build and run using the local build script:

    bash
    # 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: Using npx (Direct from GitHub)

    Run directly from GitHub without installation:

    bash
    # With inline environment variables
    CONFLUENCE_DOMAIN=your-domain.atlassian.net \
    CONFLUENCE_EMAIL=your-email@domain.com \
    CONFLUENCE_API_TOKEN=your-api-token \
    npx github:aaronsb/confluence-cloud-mcp
    
    # Or with an environment file
    npx github:aaronsb/confluence-cloud-mcp --env /path/to/.env

    Create a .env file with your Confluence credentials:

    code
    CONFLUENCE_DOMAIN=your-domain.atlassian.net
    CONFLUENCE_EMAIL=your-email@domain.com
    CONFLUENCE_API_TOKEN=your-api-token

    Option 4: From Source

    1. Install dependencies:

    bash
    npm install

    2. Configure environment variables:

    Create a .env file with your Confluence credentials:

    code
    CONFLUENCE_DOMAIN=your-domain.atlassian.net
    CONFLUENCE_EMAIL=your-email@domain.com
    CONFLUENCE_API_TOKEN=your-api-token

    3. Build the project:

    bash
    npm run build

    4. Run the server:

    bash
    node build/index.js

    Usage

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

    Using Claude Code CLI:

    bash
    claude mcp add confluence-cloud npx -- github:aaronsb/confluence-cloud-mcp --env /path/to/.env

    Using npx in MCP configuration:

    json
    {
      "mcpServers": {
        "confluence": {
          "command": "npx",
          "args": ["github:aaronsb/confluence-cloud-mcp", "--env", "/path/to/.env"],
          "disabled": false,
          "autoApprove": []
        }
      }
    }

    Using Docker:

    json
    {
      "mcpServers": {
        "confluence": {
          "command": "docker",
          "args": ["run", "--rm", "-i", "ghcr.io/aaronsb/confluence-cloud-mcp:latest"],
          "env": {
            "CONFLUENCE_DOMAIN": "your-domain.atlassian.net",
            "CONFLUENCE_EMAIL": "your-email@domain.com",
            "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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