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@mitr-analytics/mcp

@mitr-analytics/mcp

by shiv9thakur

Get an app's analytics report

get_app_report
Read-only

Fetches a 7-day analytics report for one app, including active users, KPIs, traffic, acquisition, geography, device breakdown, web vitals, and conversions for analysis and summary.

Instructions

Fetch a 7-day analytics report for one app: active users, KPIs (pageviews, unique visitors) with sparklines, traffic overview, acquisition (referrers/UTM/entry pages), geography, device/browser/OS breakdown, web vitals, and conversions. Structured data meant for you to analyze and summarize, not a canned report.

Input Schema

NameRequiredDescriptionDefault
siteIdYesThe app's siteId, from list_apps.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.3.1

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover read-only safety and closed-world behavior. The description adds valuable context beyond annotations: the fixed 7-day window, the specific data sections included, and the fact that this is structured raw data rather than a pre-summarized report.

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?

The description is front-loaded with the core action and is only two sentences. The long enumeration of report sections is informative rather than wasteful, though it could be marginally more scannable if structured as a list.

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?

With no output schema, the description carries the burden of explaining return values and does so by listing the major report categories and clarifying that the output is structured for analysis. It stops short of detailing the exact response shape, but it is sufficient for an agent to know what to expect.

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 description coverage is 100% and the single parameter siteId is documented as coming from list_apps. The description adds no additional meaning about this parameter, so the baseline score of 3 applies when the schema already handles semantics.

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

Purpose4/5

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

The description states a specific verb ('Fetch'), resource ('7-day analytics report'), and scope ('for one app'), and enumerates the report's contents. It is clear what the tool returns, but it does not explicitly contrast with siblings like get_workspace_overview, so sibling differentiation is only implicit via 'for one app'.

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 description implies usage through its content list and notes the data is 'meant for you to analyze and summarize, not a canned report', which guides output handling. However, it gives no explicit when-to-use/when-not guidance or named alternatives for similar analytics tools.

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