aaronsb confluence cloud mcp

aaronsb confluence cloud mcp avatar

by aaronsb

What is aaronsb confluence cloud mcp

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:

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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Frequently Asked Questions

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.

What are MCP Servers?

MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.

How do MCP Servers work?

MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.

Are MCP Servers secure?

Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.

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