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Use natural language to manage Jira and Confluence work and collaboration
This MCP tool is described as connecting to Atlassian Cloud services for Confluence and Jira, which implies normal MCP-style remote SaaS data interaction and local server execution. The available material is sparse, but it is open-source under MIT with no clear high-risk red flags; however, community adoption is low and maintenance status is unknown, so cautious validation is advised.
The header says there are no required keys/environment variables, yet the description claims interaction with Atlassian Cloud APIs; if true, operation would normally require some form of Atlassian credential or session configuration. The lack of documentation leaves credential sourcing, storage, and scope unclear, creating ordinary configuration/misuse concerns, but there is no explicit sign of credential theft or abuse.
The description explicitly indicates communication with Atlassian Cloud APIs for documents, search, issues, and sprint operations, so user requests and related business data will likely be sent to Atlassian cloud services. The exact domains/endpoints are not listed, which reduces transparency, but there is no evidence of exfiltration to unrelated or unknown third-party endpoints.
The system checks indicate this tool executes code, meaning a local MCP service process must run. For an MCP tool, this is a standard capability; the available material does not show requests for unusual system privileges, unrelated command execution, or obviously dangerous behavior, so this alone does not justify a high-risk rating.
Based on the description, its primary access scope should be Atlassian Cloud resources such as Confluence/Jira documents, search results, issues, and sprint data. The material does not claim broad local file read/write access, and there is no sign of permissions exceeding its stated purpose; however, the missing README prevents verification of precise access boundaries and least-privilege practices.
The project is open-source and MIT-licensed, which is a meaningful risk-reducing factor because the code can be audited. On the other hand, it comes from a third-party registry, has 0 stars, and an unknown maintenance status, so evidence of trust and maturity is limited; still, there are no clear high-risk signs such as closed source, unreachable distribution sources, or obviously malicious content.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "MCP Atlassian Server" yet — see the docs or source repo.
Please check all in-progress and blocked issues in the current sprint of the 'Mobile Redesign' Jira project and summarize status by assignee.
A list of current sprint issues with progress and blockers summarized by assignee.
Search Confluence for pages about 'release process' from the past 6 months, extract the key steps, and turn them into a concise guide.
A summary of relevant pages and a clearly structured release process guide.
Using the Jira backlog, select high-priority issues for the next sprint, suggest goals and capacity allocation, and list key risks to watch.
A proposed sprint scope with goals, capacity allocation, and risk notes.
Connect Confluence and Jira for project context, issue management, and documentation.
Manage Jira issues and Confluence pages with natural language and attachments.
Use natural language to search and manage Jira and Confluence content.
Let AI securely query, create, and manage Jira and Confluence content.
Connect Confluence and Jira to query docs, issues, and project work.
Use natural language to manage Jira issues and Confluence pages faster.