Confluence MCP Server K7o

🚀 Confluence MCP Server

An implementation of the Model Context Protocol (MCP) server for Atlassian Confluence. This server offers a set of tools to interact with Confluence via the MCP protocol, enabling AI agents to seamlessly handle Confluence content. Built with Flask, it's easy to deploy to Cloud Run.

✨ Features

• Search for pages and spaces using Confluence Query Language (CQL).
• List all available Confluence spaces.
• Create, read, update, and delete Confluence pages.
• Support rich metadata for Confluence resources.
• A Flask-based server suitable for Cloud Run deployment.
• Equipped with MCP tools for easy AI agent integration.

📦 Installation

1. Clone the repository.
2. Install the dependencies:

pip install -r requirements.txt

📚 Configuration

Create a .env file in the project root directory and add the following variables:

CONFLUENCE_URL=https://your-instance.atlassian.net/wiki
CONFLUENCE_ACCESS_TOKEN=your_access_token
PORT=8080  # Optional, default is 8080

How to obtain an access token:

1. Log in to your Atlassian account.
2. Navigate to Account Settings > Security > Create and manage API tokens.
3. Create a new API token and copy it.

💻 Usage Examples

Available MCP Tools

The server provides the following MCP tools:

1. Search Content

@tool("search_confluence")
def search(query: str) -> Dict[str, Any]

2. Get Spaces

@tool("get_spaces")
def get_spaces() -> Dict[str, Any]

3. Get Page Content

@tool("get_page_content")
def get_page_content(space_key: str, page_id: str) -> Dict[str, Any]

4. Create Page

@tool("create_page")
def create_page(space_key: str, title: str, content: str) -> Dict[str, Any]

5. Update Page

@tool("update_page")
def update_page(space_key: str, page_id: str, content: str) -> Dict[str, Any]

6. Delete Page

@tool("delete_page")
def delete_page(space_key: str, page_id: str) -> Dict[str, Any]

Run Locally

To run the server locally:

python example.py

The server will start at http://localhost:8080

Cloud Run Deployment

1. Build the Docker image:

docker build -t confluence-mcp .

2. Tag and push it to Google Container Registry:

docker tag confluence-mcp gcr.io/[PROJECT-ID]/confluence-mcp
docker push gcr.io/[PROJECT-ID]/confluence-mcp

3. Deploy to Cloud Run:

gcloud run deploy confluence-mcp \
  --image gcr.io/[PROJECT-ID]/confluence-mcp \
  --platform managed \
  --allow-unauthenticated \
  --set-env-vars="CONFLUENCE_URL=[YOUR_URL],CONFLUENCE_ACCESS_TOKEN=[YOUR_TOKEN]"

🔧 Technical Details

All tools include appropriate error handling and will return well-formatted error messages. The response format includes:

• Success: Relevant data in the specified format.
• Error: {"error": "Error message"}

⚠️ Important Note

1. Always use environment variables to store sensitive data.
2. Consider using Cloud Run's built-in key management feature.
3. Implement appropriate authentication for your endpoints.
4. Ensure the security of your Confluence access token.

🤝 Contribution Guidelines

Contributions are welcome! Please refer to the project documentation to learn how to participate in the development.

📄 License

This project is licensed under the [LICENSE] license.