Search and retrieve Confluence content using CQL queries via the MCP Atlassian Server, enabling efficient access to Confluence data within the MCP interface.
Find Confluence content by text, title, or specific space using structured queries. Filter results by body format, limit output, and enable pagination for efficient searches.
Search Confluence documentation pages using keywords to find relevant information. Filter results by specific spaces and control the number of returned items for efficient content discovery.
A Model Context Protocol server that enables AI assistants to interact with Confluence content, supporting operations like retrieving, searching, creating, and updating pages and spaces.
A model context server that provides prompts that can be used as slash commands for clients like Zed Editor, in order to add page contents as context to the AI assistant.