Confluence Wiki MCP Server Extension

The Confluence Wiki MCP Server Extension bridges the gap between AI assistants and corporate knowledge bases by turning Confluence pages into consumable Markdown for models such as Claude. In environments where documentation lives in Atlassian’s Confluence, developers and product teams often struggle to feed that content into conversational AI without manual copy‑pasting or custom scripts. This MCP server eliminates those friction points, enabling seamless retrieval and transformation of wiki content directly within an AI‑powered IDE or chat interface.

At its core, the extension exposes a lightweight MCP server that listens for tool calls issued by an AI client. When the model detects a Confluence URL in a prompt, it can invoke the server to fetch the page. The server authenticates with Confluence using credentials stored securely in an encrypted file, retrieves the HTML content, and converts it to clean Markdown. The resulting text is then streamed back to the AI model, which can summarize, analyze, or incorporate it into code generation tasks. This flow removes the need for developers to manually export pages or write custom parsers, saving time and reducing errors.

Key capabilities include:

• Secure credential handling – passwords are encrypted at rest, never exposed in editor settings or logs.
• User‑friendly configuration – a dedicated command palette wizard collects host URL, username, and password.
• Automatic Markdown conversion – raw Confluence HTML is rendered into plain Markdown, preserving headings, lists, and code blocks.
• MCP integration – the server is registered as a command‑type MCP endpoint, making it discoverable by any MCP‑compliant client such as Cursor or VSCode.

Typical use cases span the software development lifecycle. A developer might ask an AI assistant to “summarize the design guidelines from this Confluence page” and receive a concise overview without leaving their editor. Product managers can pull feature specifications into chat, while QA engineers can retrieve test plans on demand. In continuous integration pipelines, automated agents could fetch documentation updates and embed them into release notes or changelogs.

By integrating Confluence content directly into AI workflows, the extension empowers teams to leverage existing documentation without duplicating effort. Developers benefit from a single source of truth, reduced context switching, and the ability to ask natural language questions about internal knowledge bases. The combination of secure authentication, easy setup, and native MCP support makes this extension a practical addition for any organization that relies on Confluence for knowledge management.