Confluence Communication Server MCP Server: Seamless Integration with Confluence Data Sources

Overview: What is Confluence Communication Server MCP Server?

The Confluence Communication Server MCP Server is a TypeScript-based protocol implementation that bridges AI applications and specific data sources, in this case, Confluence. As an MCP (Model Context Protocol) server, it enables seamless communication between AI tools such as Claude Desktop, Continue, Cursor, and others by adhering to a standardized communication framework. This allows these applications to interact with Confluence effectively, performing tasks like executing CQL queries for searching and retrieving page content.

🔧 Core Features & MCP Capabilities

The Confluence Communication Server MCP Server offers several core features aligned with its MCP capabilities:

• execute_cql_search: A tool for running CQL (Confluence Query Language) queries to search for specific pages within Confluence.
  • Parameters: cql, limit (default value: 10).
• get_page_content: Provides functionality to fetch the content of a specified Confluence page.
  • Parameters: pageId.

These features are implemented using TypeScript, ensuring robust and maintainable code. The server is designed with compatibility in mind, supporting multiple MCP clients such as Claude Desktop, Continue, Cursor, and others.

⚙️ MCP Architecture & Protocol Implementation

The architecture of the Confluence Communication Server MCP Server revolves around adhering to the Model Context Protocol (MCP). This protocol defines a set of rules and methods that ensure consistent communication between AI applications and data sources. The server is structured to handle stdio interactions, making it easy for connected agents like Claude Desktop to execute commands.

The core components include:

• CQL Execution Module: This handles the execution of CQL queries sent from MCP clients.
• Confluence API Client: Responsible for fetching page content based on user-defined parameters.

Mermaid Diagram: MCP Protocol Flow

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

Mermaid Diagram: Data Architecture

graph TD
    A[MCP Client] --> B[send request to] --> C[MCP Server]
    C -->|process request and generate response| D[MCP Server]
    D --> E[Confluence API Client]
    E -->|fetch data| F[Data Source]
    F -->|data| G[MCP Server]
    G --> H[return data/response to] --> A

🚀 Getting Started with Installation

To set up the Confluence Communication Server MCP Server, follow these steps:

1. Clone the Repository:

   git clone https://github.com/confluence-communication-server/mcp-server.git
   

2. Install Dependencies:

   npm install
   

3. Build the Server:

   npm run build
   

4. Run for Development with Auto-Rebuild:

   npm run watch
   

5. Configure MCP Client: For use with Claude Desktop, edit the configuration file located at ~/Library/Application Support/Claude/claude_desktop_config.json or %APPDATA%/Claude/claude_desktop_config.json.

6. Add the Server Configuration:

   {
     "mcpServers": {
       "Confluence communication server": {
         "command": "node",
         "args": [
           "/PATH_TO_THE_PROJECT/build/index.js"
         ],
         "env": {
           "CONFLUENCE_URL": "https://XXXXXXXX.atlassian.net/wiki",
           "CONFLUENCE_API_MAIL": "Your email",
           "CONFLUENCE_API_KEY": "KEY_FROM: https://id.atlassian.com/manage-profile/security/api-tokens"
         }
       }
     }
   }
   

💡 Key Use Cases in AI Workflows

Use Case 1: Query and Retrieve Specific Pages

A developer might use the execute_cql_search function to find specific pages within Confluence with relevant documentation. This allows for quick access to critical information, enhancing productivity.

Use Case 2: Integrate Page Content into AI Documentation

AI applications like Continue can retrieve page contents using get_page_content. The fetched content can then be integrated into comprehensive documentation or reports generated by the application, ensuring up-to-date and accurate information is constantly available.

🔌 Integration with MCP Clients

The Confluence Communication Server MCP Server supports several well-known MCP clients:

• Claude Desktop: Fully compatible, offering seamless interaction.
• Continue: Fully compatible but limited to tool interactions due to specific API constraints.
• Cursor: Limited compatibility; only data sources/interactions are supported.

📊 Performance & Compatibility Matrix

MCP Client Compatibility

To ensure broad integration and support for various AI tools and applications:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

🛠️ Advanced Configuration & Security

MCP Server Configuration Example:

Here is a basic configuration snippet for the Confluence Communication Server:

{
  "mcpServers": {
    "Confluence communication server": {
      "command": "node",
      "args": [
        "/PATH_TO_THE_PROJECT/build/index.js"
      ],
      "env": {
        "CONFLUENCE_URL": "https://XXXXXXXX.atlassian.net/wiki",
        "CONFLUENCE_API_MAIL": "Your email",
        "CONFLUENCE_API_KEY": "KEY_FROM: https://id.atlassian.com/manage-profile/security/api-tokens"
      }
    }
  }
}

Security Considerations:

• Always ensure secure handling of API keys and configuration values.
• Implement proper error handling to prevent misuse.

❓ Frequently Asked Questions (FAQ)

1. How do I set up the Confluence Communication Server MCP Server?

   • Follow the installation instructions provided in the README, including steps for setting up dependencies and modifying configurations.

2. What are the supported MCP clients?

   • The server supports Claude Desktop, Continue, and Cursor but integrates best with Claude Desktop for full functionality.

3. How do I execute a CQL query from an AI application?

   • Use the execute_cql_search function to run queries against Confluence.

4. Can the server handle sensitive data?

   • Security measures are recommended, especially when handling API keys and sensitive information through configuration files.

5. What steps should I take if I encounter issues during setup or use?

   • Refer to the official documentation and troubleshooting section of the MCP Server GitHub repository for guidance on common issues and solutions.

👨‍💻 Development & Contribution Guidelines

Contributors can follow these guidelines:

1. Fork the repository.
2. Make your changes, ensuring they align with the protocol standards.
3. Follow code style best practices to keep the project maintainable.
4. Submit a pull request for review.

For detailed instructions and more information on development, refer to the contribution guide.

🌐 MCP Ecosystem & Resources

Explore further resources within the broader MCP ecosystem:

• MCP Protocol Documentation: Detailed understanding of protocol specifications.
• MCP Client Libraries: Additional support for integrating with various clients.

By leveraging this comprehensive MCP server, developers and AI application users can enhance their workflows through seamless integration with Confluence data.