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Confluence MCP Server

by Erato949
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Confluence MCP Server

Release Status License Platform

A universal, production-ready MCP (Model Context Protocol) server for Confluence integration. Built with FastMCP, this server provides AI assistants like Claude with direct access to Confluence Cloud functionality through multiple transport protocols and deployment options.

🌐 Universal Deployment Platform

NEW in v1.1.0: Multi-platform support with HTTP transport alongside the original stdio transport.

🚀 Deployment Options

PlatformTransportStatusUse Case
Claude Desktopstdio✅ 100% CompatibleLocal development, personal use
Smithery.aiHTTP🔧 OptimizedCloud deployment, team sharing (optimized server)
DockerHTTP/stdio✅ Production ReadyContainerized deployment
Web ClientsHTTP✅ Production ReadyBrowser-based AI tools
Cloud PlatformsHTTP✅ Production ReadyRailway, Heroku, AWS, etc.

✨ Features

  • Complete Page Management: Create, read, update, delete Confluence pages
  • Advanced Search: Search pages with CQL (Confluence Query Language) support
  • Space Management: List and explore Confluence spaces with permissions
  • Attachment Handling: Upload, download, and manage page attachments
  • Comment System: Access and manage page comments and discussions
  • Multi-Transport: stdio (Claude Desktop) + HTTP (web/cloud platforms)
  • Universal Launcher: Auto-detects best transport mode for your environment
  • Production Ready: Comprehensive error handling, logging, and monitoring

🚀 Quick Start

Option 1: Claude Desktop (stdio transport)

  1. Install Dependencies:
    pip install -r requirements.txt
  2. Configure Claude Desktop:
    { "mcpServers": { "confluence": { "command": "python", "args": ["-m", "confluence_mcp_server.main"], "env": { "CONFLUENCE_URL": "https://your-org.atlassian.net", "CONFLUENCE_USERNAME": "your-email@domain.com", "CONFLUENCE_API_TOKEN": "your-api-token" } } } }
  3. Restart Claude Desktop and look for the 🔨 hammer icon

Option 2: HTTP Server (new in v1.1.0)

  1. Install Dependencies:
    pip install -r requirements.txt
  2. Set Environment Variables:
    export CONFLUENCE_URL="https://your-org.atlassian.net" export CONFLUENCE_USERNAME="your-email@domain.com" export CONFLUENCE_API_TOKEN="your-api-token"
  3. Start HTTP Server:
    python -m confluence_mcp_server.server_http
  4. Test the Server:
    curl http://localhost:8000/health # Returns: {"status": "healthy", "transport": "http"}

Option 3: Docker Deployment (new in v1.1.0)

  1. Build Container:
    docker build -t confluence-mcp-server .
  2. Run Container:
    docker run -p 8000:8000 \ -e CONFLUENCE_URL="https://your-org.atlassian.net" \ -e CONFLUENCE_USERNAME="your-email@domain.com" \ -e CONFLUENCE_API_TOKEN="your-api-token" \ confluence-mcp-server

Option 4: Universal Launcher (new in v1.1.0)

The universal launcher automatically detects the best transport mode:

# Auto-detect transport mode python -m confluence_mcp_server.launcher # Force specific mode python -m confluence_mcp_server.launcher --http --port 9000 python -m confluence_mcp_server.launcher --stdio

Option 5: Smithery.ai Deployment (new in v1.1.0)

  1. Upload Files: Upload smithery.yaml and server code to Smithery.ai
  2. Configure Credentials: Set Confluence URL, username, and API token
  3. Deploy: Smithery.ai handles the rest automatically

🛠️ Available Tools

All 10 Confluence tools work across all transport modes (stdio and HTTP):

ToolDescriptionExample Usage
get_confluence_pageRetrieve page content"Show me the content of page ID 123456"
create_confluence_pageCreate new pages"Create a meeting notes page in the PROJ space"
update_confluence_pageModify existing pages"Add a new section to page 123456"
delete_confluence_pageRemove pages"Delete the outdated page 123456"
search_confluence_pagesSearch with CQL"Find all pages in PROJ space modified this week"
get_confluence_spacesList available spaces"What spaces do I have access to?"
get_page_attachmentsView page attachments"Show attachments on page 123456"
add_page_attachmentUpload files"Upload this document to page 123456"
delete_page_attachmentRemove files"Delete the old attachment from page 123456"
get_page_commentsRead page comments"Show me comments on page 123456"

🌐 HTTP API Endpoints (v1.1.0)

The HTTP transport provides these endpoints for web integration:

EndpointMethodDescription
/GETServer information and tool count
/healthGETHealth check and status
/mcpGETList available tools (lazy loading)
/mcpPOSTExecute tools via JSON-RPC 2.0
/mcpDELETESession cleanup

Example HTTP Usage

# List available tools curl http://localhost:8000/mcp # Execute a tool via JSON-RPC curl -X POST http://localhost:8000/mcp \ -H "Content-Type: application/json" \ -d '{ "jsonrpc": "2.0", "id": 1, "method": "tools/call", "params": { "name": "get_confluence_spaces", "arguments": {"limit": 10} } }'

💬 Example AI Assistant Conversations

Creating a Page (works on all platforms):

You: Create a new project kickoff page in the ENGINEERING space with a basic template AI: I'll create a project kickoff page for you in the ENGINEERING space... [Uses create_confluence_page tool] ✅ Created "Project Kickoff" page (ID: 789123) in ENGINEERING space

Searching Content:

You: Find all pages mentioning "API documentation" that were updated this month AI: I'll search for pages with "API documentation" updated recently... [Uses search_confluence_pages tool] 📄 Found 5 pages matching your criteria...

🔧 Configuration Options

Platform Compatibility Notes

Cursor: Requires installation path with no spaces. Your current path C:/Users/chris/Documents/Confluence-MCP-Server_Claude is compatible.

Windsurf: Full MCP support with both stdio and HTTP transports.

Smithery.ai: Uses HTTP transport with automatic configuration management.

Claude Desktop: Uses stdio transport with manual configuration.

Environment Variables (all platforms)

CONFLUENCE_URL=https://your-org.atlassian.net CONFLUENCE_USERNAME=your-email@domain.com CONFLUENCE_API_TOKEN=your-api-token

.env File Support

# .env file in project root CONFLUENCE_URL=https://your-org.atlassian.net CONFLUENCE_USERNAME=your-email@domain.com CONFLUENCE_API_TOKEN=your-api-token

Smithery.ai Configuration

The server automatically handles base64-encoded configuration from Smithery.ai platform.

🔒 Security & Authentication

  • API Tokens: Secure token-based authentication with Confluence
  • HTTPS Only: All API requests use encrypted connections
  • Permission Inheritance: Server inherits your Confluence user permissions
  • No Data Storage: Direct API passthrough, no local data retention
  • Container Security: Non-root user, minimal attack surface

Getting Confluence API Token

  1. Go to Atlassian Account Settings
  2. Click "Create API Token"
  3. Copy the generated token
  4. Use your email address as the username

🧪 Testing & Validation

Run Test Suite

# Run all tests python -m pytest tests/ -v # Test HTTP transport specifically python -m pytest tests/test_http_transport.py -v # Test specific functionality python -m pytest tests/ -k "test_get_page"

Validate Dependencies

python -c " import fastmcp, fastapi, uvicorn, pytest_asyncio; print('✅ All dependencies working correctly') "

Health Checks

# stdio transport (Claude Desktop) python -c "import confluence_mcp_server.main; print('✅ stdio transport ready')" # HTTP transport python -m confluence_mcp_server.server_http & curl http://localhost:8000/health

🔄 Migration from v1.0.x

100% Backward Compatible - no changes needed for existing Claude Desktop setups.

New capabilities in v1.1.0:

  • ✅ HTTP transport for web/cloud deployment
  • ✅ Docker containerization
  • ✅ Smithery.ai integration
  • ✅ Universal launcher
  • ✅ Enhanced configuration management
  • ✅ Production monitoring and health checks

🐛 Troubleshooting

Claude Desktop Issues

  • No hammer icon: Check config file syntax and restart Claude Desktop
  • Authentication fails: Verify API token and Confluence URL
  • Tools fail: Check environment variables and network connectivity

Cursor Issues

  • "No tools found": Ensure installation path contains no spaces
    • ❌ node C:/my projects/mcpserver/build/index.js (fails due to space)
    • ✅ node C:/projects/mcpserver/build/index.js (works)
  • Windows paths: Use forward slashes or properly escaped backslashes
  • Test manually first: Verify server starts without errors before adding to Cursor
  • Check task manager: Look for briefly appearing node processes during refresh

HTTP Server Issues

  • Port conflicts: Use --port flag to specify different port
  • CORS errors: Server includes CORS middleware for web clients
  • Tool execution fails: Check environment variables and Confluence permissions

Docker Issues

  • Container won't start: Check environment variables are properly set
  • Health check fails: Verify Confluence connectivity from container
  • Permission errors: Container runs as non-root user by default

General Debugging

# Enable debug logging export LOG_LEVEL=DEBUG python -m confluence_mcp_server.launcher # Test Confluence connectivity curl -u email:token https://your-org.atlassian.net/rest/api/space

📦 Production Deployment

Cloud Platforms

Railway:

# Deploy directly from GitHub railway login railway link railway up

Heroku:

# Use included Dockerfile heroku container:push web heroku container:release web

AWS/GCP/Azure:

  • Use Docker image for container services
  • Set environment variables in platform configuration
  • Use health check endpoint /health for monitoring

Monitoring

The HTTP server provides monitoring endpoints:

  • Health: GET /health - Server status
  • Metrics: GET / - Tool count and server info
  • Logs: Structured logging for debugging and monitoring

🤝 Development

Project Structure

confluence_mcp_server/ ├── main.py # stdio transport (Claude Desktop) ├── server_http.py # HTTP transport (web/cloud) ├── launcher.py # Universal launcher ├── mcp_actions/ # Tool implementations │ ├── page_actions.py # Page management │ ├── space_actions.py # Space operations │ ├── attachment_actions.py # File handling │ ├── comment_actions.py # Comments │ └── schemas.py # Data models └── utils/ └── logging_config.py # Logging setup tests/ # Comprehensive test suite ├── test_http_transport.py # HTTP transport tests └── test_*.py # Tool-specific tests Dockerfile # Container configuration smithery.yaml # Smithery.ai deployment pyproject.toml # Package configuration requirements.txt # Dependencies

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Add tests for new functionality
  4. Ensure all tests pass (pytest tests/ -v)
  5. Test both stdio and HTTP transports
  6. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🚀 Ready to Get Started?

Choose your deployment option:

  • 🖥️ Claude Desktop: Use the stdio transport for local development
  • 🌐 Web/Cloud: Use the HTTP transport for scalable deployment
  • 🐳 Docker: Use containers for consistent deployment
  • ⚡ Smithery.ai: Use cloud platform for instant deployment

Transform your Confluence workflow with AI assistance today! 🎉

This server cannot be installed

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security - not tested
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license - not found
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quality - not tested

A universal, production-ready MCP server that provides AI assistants like Claude with direct access to Confluence Cloud functionality for creating, reading, updating, and managing content through multiple transport protocols.

  1. 🌐 Universal Deployment Platform
    1. 🚀 Deployment Options
  2. ✨ Features
    1. 🚀 Quick Start
      1. Option 1: Claude Desktop (stdio transport)
      2. Option 2: HTTP Server (new in v1.1.0)
      3. Option 3: Docker Deployment (new in v1.1.0)
      4. Option 4: Universal Launcher (new in v1.1.0)
      5. Option 5: Smithery.ai Deployment (new in v1.1.0)
    2. 🛠️ Available Tools
      1. 🌐 HTTP API Endpoints (v1.1.0)
        1. Example HTTP Usage
      2. 💬 Example AI Assistant Conversations
        1. 🔧 Configuration Options
          1. Platform Compatibility Notes
          2. Environment Variables (all platforms)
          3. .env File Support
          4. Smithery.ai Configuration
        2. 🔒 Security & Authentication
          1. Getting Confluence API Token
        3. 🧪 Testing & Validation
          1. Run Test Suite
          2. Validate Dependencies
          3. Health Checks
        4. 🔄 Migration from v1.0.x
          1. 🐛 Troubleshooting
            1. Claude Desktop Issues
            2. Cursor Issues
            3. HTTP Server Issues
            4. Docker Issues
            5. General Debugging
          2. 📦 Production Deployment
            1. Cloud Platforms
            2. Monitoring
          3. 🤝 Development
            1. Project Structure
            2. Contributing
          4. 📄 License
            1. 🚀 Ready to Get Started?

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