@lodd/mcp-server

get_timeseries

Retrieve visitor and page view counts over time, bucketed hourly or daily, with optional filters by country, browser, OS, device, UTM source, or referrer.

Instructions

Get visitor and page view counts bucketed over time (hourly or daily). Returns an array of {date_label, page_views, unique_visitors} objects. Optional filters segment by country, browser, os, device type, UTM source, or referrer.

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_timeseries"
  }
}

Input Schema

Name	Required	Description	Default
`site`	Yes	Site domain or UUID
`period`	No	Time period	30d
`interval`	No	Bucket interval. Auto-selected based on period if omitted.
`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 correctly describes the output and filters but omits potential behaviors like latency, rate limits, or permission requirements. For a read operation this is minimally adequate but lacks depth.

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: first states purpose and return format, second lists filters. No redundant information. Front-loaded with key value. Every sentence earns its place.

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 no output schema and no annotations, the description provides a good overview. It covers the return shape, available filters, and interval behavior. Could mention pagination or limits, but for a straightforward time-series tool this is largely sufficient.

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%, so the description does not need to repeat all parameter details. However, it adds value by summarizing filter types in a list and noting that interval auto-selects based on period, which is not in the schema description. This goes beyond the schema.

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?

Clearly states verb 'Get', resource 'visitor and page view counts bucketed over time', and specifies return format. Distinguishes from siblings like get_realtime (real-time) and get_snapshot (point-in-time) by focusing on time-bucketed data.

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?

No explicit when-to-use or when-not-to-use guidance. The description implies usage for historical trends but does not contrast with alternative tools like get_analytics or get_event_timeseries. Context is implied by the tool name and sibling list, but not stated.

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