Atlassian Rovo MCP server connects Jira, Confluence, and other Atlassian context to AI assistants through MCP. It is meant for people who want an AI client, IDE, or agent platform to work with Atlassian information without leaving the tool they are already using.
The server is described as securely connecting Atlassian products with an LLM, IDE, or agent platforms of choice. Supported examples on the page include Cursor, VS Code, ChatGPT, and Claude. Within those clients, it can be used to reference Jira issues, pull specs, log work, search and create Jira issues, summarize Jira issues, and bring Jira and Confluence into research and coding workflows. The page also says it can help summarize work across Atlassian and create new Confluence pages or Jira work items in bulk.
Security and access control are part of the offering. Atlassian says the official remote MCP server is secured with OAuth authentication and granular permission controls. It also provides a default list of supported AI domains, and administrators can add or block domains to create a trusted list that matches organizational security policies.
The page presents the product as an official remote MCP server and says it can be added to supported AI clients in a single click. It is offered by Atlassian and is shown with a free entry point on the page. The description frames it as a way to connect the Atlassian Platform into trusted AI tools so information spanning people, services, knowledge, and work is available inside those clients.
Atlassian Rovo MCP server sits in PulseGate's API design, testing & docs category. It allows AI assistants to securely access and utilize Atlassian data and context through standardized MCP tools. It is built as a B2B product for developers integrating AI assistants with Atlassian products. It ships for the web and API.
It is developed by Atlassian, and it first shipped in 2025. The project is developed in the open on GitHub with 818 stars and 28 commits in the last 90 days. Among its 4 catalogued features are MCP server, atlassian data access, and AI assistant integration. The interface is available in 12 languages, including German, English, and Spanish. It exposes integrations via an MCP server and a public API.
Summary written by a language model from the project’s public pages.
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