MCP Analytics Improvements
under review
Ramesh Lokesh
The current MCP Server Analytics dashboard provides a solid baseline, but one of our customers feels that there are several gaps that limit its usefulness for admins managing real-world deployments. They would like to request the following improvements:
Break down MCP usage by user role (Owner, Admin, Editor, etc.) and distinguish Reader vs Team Member activity separately, so admins can understand who is driving usage and plan enablement accordingly.
Add a geographic and timezone distribution view to help global teams correlate failure spikes or usage patterns with specific regions.
Surface which articles and categories are being accessed through MCP tools — not just which tools are called — to identify content gaps and validate whether AI assistants are reaching the right information.
For multi-project accounts, introduce a workspace-level filter or cross-project summary so admins can compare MCP activity without switching between projects.
Extend export beyond PNG chart images to full CSV downloads across call logs, tool usage, and user activity, enabling use in external reporting and BI tools.
Add a "Compare to previous period" toggle so adoption trends can be tracked week-over-week or month-over-month directly within the dashboard.
Surface token consumption per user and per client alongside call volume so admins can proactively manage plan limits before failures occur.
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D360 Product Management
updated the status to
under review
M
Mukesh Sriram
Hi Thistle Gazelle , Ramesh Lokesh,
Thank you for sharing this detailed feedback.
We understand the need for richer MCP Server Analytics to help administrators better understand adoption, usage patterns, and operational insights across their deployments.
This request is currently under review. We're evaluating the feasibility of enhancing the analytics experience with capabilities such as user and role-based insights, geographic and workspace-level reporting, content access analytics, expanded export options, trend comparisons, and token consumption metrics based on customer feedback and real-world usage scenarios.
We'll share updates once we have more clarity from our assessment.
Ramesh Lokesh
Thistle Gazelle