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friendlygeorge

plausible-mcp-server

query_stats

Query Plausible analytics with full flexibility — specify metrics, dimensions, filters, and date ranges for custom stats.

Instructions

Query Plausible analytics with full flexibility — metrics, dimensions, filters, date ranges. The main stats endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (default: 100, max: 10000)
filtersNoFilters like 'visit:source==Google', 'event:page==/blog', 'visit:country_name==United States'
includeNoInclude extra fields: 'events', 'page', 'custom_props'
metricsYesMetrics to calculate: visitors, visits, pageviews, views_per_visit, visit_duration, events, bounce_rate, scroll_depth, conversion_rate
site_idYesThe site ID (domain) to query, e.g. 'example.com'
order_byNoOrder results, e.g. [['visitors', 'desc']]
date_rangeYesDate range: 'today', 'yesterday', '7d', '30d', 'month', 'year', 'all', or 'YYYY-MM-DD,YYYY-MM-DD'
dimensionsNoGroup by dimensions: visit:source, visit:referrer, visit:utm_source, visit:utm_medium, visit:utm_campaign, visit:utm_content, visit:utm_term, visit:country_name, visit:city_name, visit:screen, visit:browser, visit:browser_version, visit:os, visit:os_version, visit:entry_page, visit:exit_page, event:page, event:name, event:goal, event:props:<key>
Behavior2/5

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

With no annotations, the description must disclose behaviors like auth requirements, rate limits, or error handling. It only states flexibility and endpoints, omitting critical operational details.

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 a single concise sentence that conveys the core purpose and capabilities without unnecessary words.

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

Completeness2/5

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

For an 8-parameter tool with no output schema, the description is too brief. It lacks details on return format, pagination, or behavior with many parameters, leaving the agent underinformed.

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 coverage is 100%, so the description adds little beyond summarizing the params. It provides a high-level overview but no new semantic details beyond the schema's already thorough descriptions.

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 it queries Plausible analytics with full flexibility and explicitly calls it 'the main stats endpoint', distinguishing it from more specific sibling tools like get_breakdown or get_timeseries.

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 it is the go-to tool for flexible stats queries but provides no explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among siblings.

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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