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MCP Server By TestMu AI

by com.lambdatest.mcp
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Get Analytics Data

getAnalyticsData
Read-only

Summarises web automation test results in a date range: total tests, passed, failed, completed without a pass/fail mark, pass rate (passed over all tests, as the Insights page shows it), pass rate over tests marked passed or failed, average duration and distinct builds, grouped by status, browser, os, build, device or day. Computed from the automation test list (up to 5000 tests per call; the total is always exact).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toDateNoEnd date, YYYY-MM-DD. Defaults to today.
groupByNoDimension to group by. Defaults to status.
fromDateNoStart date, YYYY-MM-DD, within the last 59 days (older results are not served). Defaults to 30 days before toDate.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / fromDate / description
      Previous value: -"Start date, YYYY-MM-DD. Defaults to 30 days before toDate."New value: +"Start date, YYYY-MM-DD, within the last 59 days (older results are not served). Defaults to 30 days before toDate."
  2. Changed4 schema fields changed
    • changedInput schema / properties / fromDate / description
      Previous value: -"Start date (ISO 8601 format, e.g. 2024-01-01)"New value: +"Start date, YYYY-MM-DD. Defaults to 30 days before toDate."
    • changedInput schema / properties / groupBy / description
      Previous value: -"Dimension to group results by (e.g., browser, os, status)"New value: +"Dimension to group by. Defaults to status."
    • addedInput schema / properties / groupBy / enum
      Added value: +[
+  "status",
+  "browser",
+  "os",
+  "build",
+  "device",
+  "day"
+]
    • changedInput schema / properties / toDate / description
      Previous value: -"End date (ISO 8601 format)"New value: +"End date, YYYY-MM-DD. Defaults to today."
  3. First observed

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), and the description usefully adds operational context: it is computed from the automation test list, capped at 5000 tests per call, yet the total is always exact, and pass rate is defined to match the Insights page. This clarifies how the numbers are derived rather than just repeating annotation hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence that opens with the verb and then lists metrics and grouping options compactly. Dense but every clause carries information; no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description carries the burden of explaining returns, and it does so thoroughly by naming each aggregated metric and the possible grouping dimensions. Minor gap: it does not describe the shape of the returned records per group, but otherwise complete for a read-only analytics tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the parameter descriptions already document formats, defaults, and the 59-day retention limit for fromDate. The description adds no parameter-level detail beyond restating the date-range grouping, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Summarises web automation test results') and enumerates the exact metrics produced (total, passed, failed, pass rates, avg duration, distinct builds) plus the group-by dimensions. This makes it clearly distinguishable from siblings such as getTestTrends, getFlakyTests, and getAnalyticsErrors without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The date-range scope and aggregate nature imply when the tool applies, but there is no explicit when-to-use versus alternatives guidance and no mention of getTestTrends or getAnalyticsErrors as related options. Usage is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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