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Mad7droid

Clarity MCP Server

by Mad7droid

get_clarity_insights

Get Microsoft Clarity dashboard insights for the last 1-3 days: traffic, scroll depth, engagement, rage/dead clicks, and script errors, with optional breakdown by up to three dimensions and URL filter.

Instructions

Fetch Microsoft Clarity dashboard insights (traffic, scroll depth, engagement time, rage/dead clicks, script errors, etc.) for the last 1-3 days, optionally broken down by up to 3 dimensions. IMPORTANT: Clarity's API only supports a rolling 1-3 day lookback (no custom date ranges), and this project is limited to 10 requests per day total, so batch dimensions thoughtfully rather than making repeated calls. Optional urlFilter applies a case-insensitive substring match on the URL field AFTER Clarity returns its response (post-processing only) — results are still capped at Clarity's 1,000-row response limit, so a very broad urlFilter on a large site can still be affected by rows Clarity already dropped before filtering ever sees them. If urlFilter is set and none of dimension1-3 is 'URL', it's auto-added to the first open slot; if all 3 are already used by other dimensions, the call fails with an error asking you to free a slot.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numOfDaysYesHow many days back to pull data for: 1 = last 24h, 2 = last 48h, 3 = last 72h.
urlFilterNoCase-insensitive substring match on the URL field, applied AFTER Clarity returns data (post-processing only).
dimension1NoOptional first breakdown dimension.
dimension2NoOptional second breakdown dimension.
dimension3NoOptional third breakdown dimension.
Behavior5/5

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It extensively discloses rate limits, API lookback restrictions, urlFilter being post-processing only, the 1,000-row cap, auto-adding a URL dimension, and the failure mode when dimension slots are full. This is highly transparent.

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

Conciseness5/5

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

Every sentence in the description earns its place, covering purpose, constraints, rate limits, and edge cases in a logical order (purpose → important limitations → urlFilter specifics). It is dense but not verbose, and front-loaded with the core purpose.

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, but the description gives a reasonable sense of return content ('traffic, scroll depth, ...') and thoroughly covers operational caveats (rate limits, filtering, dimension slots). It does not detail response structure, but for a dashboard insights fetch, the provided context is nearly complete.

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

Parameters4/5

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

Schema coverage is 100% (all 5 parameters documented), so the baseline is 3. The description adds significant value by explaining urlFilter's post-processing behavior and the auto-add/failure interplay with dimensions, which the schema alone does not convey.

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?

The description opens with a specific verb ('Fetch') and a named resource ('Microsoft Clarity dashboard insights'), enumerating sample metrics (traffic, scroll depth, etc.) and explicitly scoping to 'last 1-3 days' with 'up to 3 dimensions'. This clearly distinguishes the tool's function from sibling tools like get_clarity_historical_insights.

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

Usage Guidelines4/5

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

The description provides clear usage context: rolling 1-3 day lookback, a 10-requests/day project limit, and explicit advice to 'batch dimensions thoughtfully rather than making repeated calls'. It implies the tool is for recent data only but does not explicitly name sibling tools as alternatives.

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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