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Overview

The Analytics dashboard gives you aggregate insights about your MCP server usage through interactive charts and summary cards. Unlike Traffic Logs (which show individual requests), Analytics shows trends and patterns over time. Access account-level analytics from Analytics in the dashboard sidebar. Per-server analytics are available on the Analytics tab of any server detail page. All charts are built with Recharts and are fully interactive — hover over any data point to see exact values.

Time range presets

All charts and KPI metrics update to reflect the selected time range:
PresetData shownGranularity
24HPast 24 hoursHourly data points
7D (default)Past 7 daysDaily data points
30DPast 30 daysDaily data points
90DPast 90 daysDaily data points

Account-level analytics

The account-level view aggregates data across all your servers.

KPI cards

Four headline metric cards are displayed at the top of the dashboard. Each card shows the current value and a percentage change compared to the previous period of equal length:
CardWhat it measuresColour logic
Total RequestsCumulative tool calls in the selected periodTrend arrow (green for increase, red for decrease)
Error RatePercentage of calls that resulted in an errorGreen when low, yellow when moderate, red when high
Avg LatencyMean execution time across all tools and serversGreen when fast, yellow when moderate, red when slow
Active ServersCount of servers that received at least one requestStatic count

Request trend chart

Type: Area chart with dual series An area chart with two overlapping series:
SeriesColourDescription
RequestsBlue (#0485f7)Total request count per time bucket
ErrorsRed (#ff383c)Error count per time bucket
  • X-axis: Time (formatted as date or hour depending on the preset)
  • Y-axis: Request count (auto-scaled, large numbers formatted as K/M)
  • Hover tooltip: Shows exact values for requests and errors at that point
Use this chart to spot sudden spikes, drops, or error surges. A gap between the blue and red areas is healthy — it means most requests are succeeding.

Latency trend chart

Type: Multi-line chart with three series
SeriesColourStyleDescription
Avg latencyBlue (#0485f7)Solid lineMean execution time
P95 latencyYellow (#fbbf24)Dashed line95th percentile — worst case for 95% of requests
P99 latencyRed (#ff383c)Dashed line99th percentile — worst case for 99% of requests
  • X-axis: Time
  • Y-axis: Latency in ms (auto-formatted: ms below 1000, seconds above)
  • Hover tooltip: Shows all three values formatted in milliseconds
Watch the P95 line, not just the average. A rising P95 with a flat average means a subset of requests are getting slow — often a database query missing an index or a rate-limited upstream API.

Top tools chart

Type: Horizontal bar chart Shows the top 8 most-called tools across all servers, ranked by total request count.
  • X-axis: Request count
  • Y-axis: Tool names
  • Colour: Blue (#0485f7)
This is the clearest signal of which tools the AI is actually using. In practice you’ll usually find that 80% of calls go to 2–3 tools — invest optimisation effort there.

Top servers chart

Type: Horizontal bar chart Shows the top 8 most-called servers by request count.
  • X-axis: Request count
  • Y-axis: Server subdomains
  • Colour: Green (#22c55e)

Geographic distribution chart

Type: Horizontal bar chart Shows the top 10 countries by request origin, using ISO 2-letter country codes.
  • X-axis: Request count
  • Y-axis: Country codes (e.g. US, DE, JP)
Useful for understanding where your users are and for diagnosing region-specific latency issues.

Server-level analytics

Click any server from the Top servers chart, or open a server’s Analytics tab, to see analytics scoped to that specific server.

Server KPI cards

CardWhat it measures
Total RequestsCalls received by this server in the period
Error RatePercentage of calls that failed
Avg LatencyMean execution time for this server’s tools
Max ConcurrencyPeak number of simultaneous active sessions

Request trend

Same dual-area chart (requests + errors) as account level, scoped to this server.

Tool breakdown

Type: Horizontal bar chart Shows the distribution of calls across this server’s tools — up to the top 10. Use this to:
  • Find tools with zero calls — bad description? unused feature?
  • Understand AI behaviour — a tool called unexpectedly often may have a too-broad description
  • Prioritise optimisation — focus on the most-called tools first

Session trend

Type: Area chart An area chart of unique client sessions over time. A session is a single AI client connection identified by the mcp-session-id header. Reading the chart:
  • Rising sessions = more clients connecting → growing adoption
  • Flat sessions + rising requests = each session is more active → more intensive use per user

Traffic by hour

Type: Bar chart A bar chart showing average request count by hour of day (0–23, in your local timezone). Use this to:
  • Understand peak usage hours
  • Plan maintenance windows during low-traffic periods
  • Identify unusual activity patterns (e.g. unexpected traffic at 3 AM)

Chart interaction

All charts support:
  • Hover tooltips — hover over any data point to see exact values with proper formatting
  • Auto-scaling — Y-axes adjust automatically based on data range
  • Number formatting — large numbers shown as K (thousands) or M (millions)
  • Time formatting — dates shown as Mar 15, hours shown as 14:00
  • Latency formatting — values below 1000 shown in ms, above shown in seconds
  • Responsive sizing — charts resize to fit the available width
  • Loading skeletons — skeleton placeholders while data is being fetched

Using analytics effectively

Identify optimisation targets: Look at P95 latency. If it’s over 3–5 seconds for any time period, your tools are too slow for a good user experience. Check the tool breakdown to find the culprit, then investigate query indexes, pagination, or caching. Find unused tools: In the tool breakdown, zero-call tools over 30 days are candidates for cleanup or improved descriptions. The AI may not be calling them because the description doesn’t match what users ask for. Debug sudden error spikes: Find the time window when errors spiked in the request trend chart, then open Traffic Logs filtered to that window to see the individual failing requests. Track adoption: Watch the session trend over time. Combine it with geographic distribution to understand where your users are and how usage is growing.