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Glama

plausible-analytics

by io.usefulapi

Timeseries

plausible_timeseries
Read-only

Convenience: metrics over time, grouped by a time interval. Plausible: POST /api/v2/query with dimensions=[interval].

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersNoOptional filters. Each is an array like ["is","visit:country_name",["Estonia"]] or ["contains","event:page",["/blog"]] with logical wrappers ["and",[...]] / ["or",[...]] / ["not",[...]]. Operators: is, is_not, contains, contains_not, matches, matches_not, has_done, has_not_done.
metricsYesMetrics to compute. Any of: visitors, visits, pageviews, views_per_visit, bounce_rate, visit_duration, events, scroll_depth, percentage, conversion_rate, group_conversion_rate, average_revenue, total_revenue, time_on_page.
site_idYesThe site's domain as registered in Plausible, e.g. "example.com".
intervalNoTime bucket to group by. Default time:day.
date_rangeYesDate range: a shortcut string ("day", "7d", "28d", "30d", "91d", "month", "6mo", "12mo", "year", "all", "24h") OR a 2-element ISO8601 array like ["2024-01-01","2024-07-01"] (dates or datetimes with tz).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

The readOnlyHint annotation already discloses that this is a safe read operation. The description adds that it uses POST /api/v2/query with dimensions=[interval], which gives insight into the underlying API call, but it does not describe output format, pagination, or other behavioral traits. This is acceptable given annotations but not rich.

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?

The description is two efficient sentences, front-loaded with the core purpose and backed by the API detail. Every word earns its place with no redundancy or filler.

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

Completeness3/5

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

For a tool with 5 params and no output schema, the description provides the essential core but lacks context on when to prefer it over siblings, what the returned rows look like, or any caveats like timezone handling. The rich schema and readOnlyHint mitigate this somewhat, making it minimally adequate but not 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?

The input schema has 100% description coverage, so parameters like interval, metrics, and date_range are already well documented. The description only mentions grouping by time interval, which adds no new meaning beyond what the schema's interval parameter already states. Baseline 3 is appropriate.

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 clearly states this tool returns metrics over time grouped by an interval, distinguishing it from the sibling aggregate and breakdown tools. However, it lacks a strong verb like 'retrieve' or 'fetch', using 'Convenience' instead, which slightly weakens clarity.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool versus alternatives such as plausible_aggregate or plausible_breakdown. The word 'Convenience' implies a wrapper, but there is no stated context, exclusions, or comparison with sibling tools.

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

All plausible-analytics toolsInspect
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TDQS

A3.7/5.0
Disambiguation4/5

Tools are mostly distinct: aggregate, breakdown, timeseries, and realtime_visitors each serve a specific query pattern, while query_stats is the general-purpose fallback. Minor overlap exists because query_stats can reproduce what the convenience wrappers do, but descriptions clarify the intended use.

Naming Consistency4/5

All tools share the plausible_ prefix and use lowercase with underscores, which is consistent. However, some names are single verbs/nouns (aggregate, breakdown, timeseries) rather than a uniform verb_noun pattern like list_sites, so there's a slight stylistic inconsistency.

Tool Count5/5

8 tools is a well-scoped size for an analytics server. It covers the main query types (totals, breakdowns, time series, realtime) plus site and goal listing, without being bloated or insufficient.

Completeness4/5

The server covers the core analytics surface: querying metrics with aggregation, breakdown, timeseries, and realtime, plus site and goal metadata. Minor gaps exist like goal creation or site management, but these are likely outside the intended read-only analytics scope.

Resources