@lodd/mcp-server

get_event_counts

Retrieve a summary of custom events for a site, showing total count and unique sessions per event. Optionally filter by country, browser, OS, device type, UTM source, or referrer.

Instructions

Get a summary of all custom events tracked on a site, showing event names with their total count and unique sessions. Optionally segment by country, browser, os, device type, UTM source, or referrer (matched against the session's page views).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "site": "<site>"
    },
    "name": "get_event_counts"
  }
}

Input Schema

Name	Required	Description	Default
`site`	Yes	Site domain or UUID
`period`	No	Time period	30d
`filter_os`	No	OS substring match (e.g. 'iOS')
`filter_browser`	No	Browser substring match (e.g. 'Chrome')
`filter_country`	No	2-letter country code (e.g. 'US')
`filter_utm_source`	No	Exact UTM source (e.g. 'twitter')
`filter_device_type`	No	Device type: 'desktop' \| 'mobile' \| 'tablet'
`filter_referrer_contains`	No	Referrer substring (e.g. 'google')

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.15Jul 28, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations provided, so the description carries full burden. It describes the output (event names, total count, unique sessions) and notes segmentation matches session page views. However, it lacks details on potential limitations, pagination, or result ordering. For a read-only tool, it is moderately 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?

Two sentences with no fluff. The first sentence states the main action and output; the second adds optionality. Information is front-loaded and efficient.

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?

Given eight parameters, no output schema, and no annotations, the description covers the key output fields (event names, total count, unique sessions) and segmentation. It lacks details on output format or limits, but for a summary tool it is largely complete.

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%, so baseline is 3. The description adds context about segmentation options but does not significantly deepen parameter understanding beyond what the schema already provides.

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 clearly states the tool returns a summary of custom events with counts and unique sessions, and lists optional segmentation dimensions. It distinguishes from siblings like get_events and get_event_timeseries which likely provide raw events or time series data.

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 implies usage for aggregated event summaries with optional filtering, but does not explicitly contrast with sibling tools. The context of siblings like get_events and get_event_timeseries provides implicit guidance, but explicit when-to-use/alternatives would improve it.

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