Confluence MCP Server Example
LocalAbout Confluence MCP Server Example
Confluence MCP Server Example is a Spring Boot AI example server for managing Confluence Cloud content. It exposes document operations as callable tools and can be tested with MCP clients such as Claude desktop app.
Key features
- 01Confluence Cloud integration
- 02Space listing
- 03Document creation
- 04Tool registration with @Tool
Use cases
- 01List Confluence Cloud spaces
- 02Create Confluence documents
- 03Test Confluence operations from an MCP client
MCP support
The server exposes Confluence Cloud management operations as tools for MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEConfluence MCP Server Example
This repository contains the complete source code for our Confluence MCP Server example built with Spring Boot AI. The server integrates with Confluence Cloud and exposes various document management operations as callable tools using the @Tool annotation. You can test this server with any MCP client, including the Claude desktop app.
For a detailed explanation on how to build an MCP server, check out our blog:
Build MCP Servers with Spring Boot AI: A Beginner’s Guide
Features
- Confluence Cloud Integration: Connects to Confluence Cloud to manage spaces, pages, and document history.
- Callable Tools: Exposes operations like listing spaces and creating documents using the
@Toolannotation. - Tool Registration: Uses
ToolCallbackProviderto register the available service methods with the MCP framework. - Testable with MCP Clients: Easily test the server using any MCP client, including the Claude desktop app.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.