Atlassian MCP server integrationAtlassian MCP server dashboards for Jira and Confluence reporting
Connect the Atlassian MCP server to Chartbrew to explore Jira issues and Confluence pages. Build project reports from approved tools that return usable issue or page data.
What You Can Track
What you can report on with Atlassian MCP
Use these reporting ideas when the connected server exposes the required read tools and fields. Tool access, account permissions, and result limits determine what you can retrieve.
Issue status
Group returned Jira issues by workflow status.
Team workload
Compare issue counts by assignee or team.
Project backlog
List unresolved work within a defined project scope.
Priority review
Separate high-priority issues from the rest of the backlog.
Recent issue changes
Inspect issue update dates for a project review.
Confluence content
List pages returned from selected spaces for documentation reviews.
How It Works
From Atlassian MCP connection to live dashboard
The Atlassian MCP workflow is built around a source connection, reusable datasets, scheduled refreshes, and shareable dashboards.
Connect the MCP server
Select Atlassian from the MCP connection list in Chartbrew. Use an Atlassian Cloud account with access to the required Jira projects and Confluence spaces. Your organization must allow the MCP connection. Review the tools after authentication.
Review and approve read tools
Test the connection and inspect the discovered tools. Approve the tools needed for AI exploration and datasets. Server access alone does not approve every tool.
Preview a dataset
Choose a tool, set its arguments, and preview the response. Select the output rows and fields. Check dates, units, filters, and result limits before saving.
Build and share the report
Create charts from the saved dataset. Add them to a dashboard, set a refresh schedule, and share the report with the intended viewers.
Why Chartbrew for Atlassian MCP
Use Atlassian MCP results in recurring reports
Bring Jira and Confluence reporting into a report that your team can inspect and share.
Control tool access
Approve read tools for the reporting task and review changes when the server tool definitions change.
Inspect the source result
Keep tool arguments and output selection available for review instead of relying only on an AI summary.
Reuse reporting datasets
Build charts from saved tool configurations when the response has suitable rows and fields.
Compare with other sources
Place Atlassian MCP results beside revenue, product, or operational data from other connections.
Refresh saved results
Schedule dataset updates. Refreshes still depend on valid authentication, tool approval, and provider limits.
Share selected results
Give report viewers the dashboard data they need without asking them to configure an MCP connection.
Setup Requirements
Connect Atlassian MCP
Use an Atlassian Cloud account with access to the required Jira projects and Confluence spaces. Your organization must allow the MCP connection. Review the tools after authentication.
Catalogue server URL: https://mcp.atlassian.com/v2/mcp
Permission to read the source records and approve the required tools in Chartbrew
A tool response with usable rows or structured fields; a prose answer alone may not work as a dataset
A defined reporting scope, date range, and plan for result limits; MCP results are not automatically paginated
Example datasets
| Dataset idea | What it can power |
|---|---|
| Issue status | Group returned Jira issues by workflow status. |
| Team workload | Compare issue counts by assignee or team. |
| Project backlog | List unresolved work within a defined project scope. |
| Priority review | Separate high-priority issues from the rest of the backlog. |
| Recent issue changes | Inspect issue update dates for a project review. |
| Confluence content | List pages returned from selected spaces for documentation reviews. |
Setup Guide
Read how external MCP connections work in Chartbrew v6
See the difference between bringing external MCP data into Chartbrew and connecting an AI app to Chartbrew's own server.
Related Features
Tools for Atlassian MCP reporting
Use Atlassian MCP dashboards with Chartbrew automation, AI workflows, sharing, embeds, filters, and reporting tools.
Related Integrations
Related data sources
Blend Atlassian MCP metrics with product, customer, revenue, analytics, project, and operational data from other Chartbrew sources.
FAQ
Atlassian MCP integration questions
Practical details about using Atlassian MCP data in Chartbrew dashboards.
Connect Atlassian MCP
Build a report from your Atlassian MCP server
Connect the server, approve read tools, and check your first dataset before you build the dashboard.
