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Plausible Analytics MCP Server

by go-ai-now

Plausible: check site access

plausible_check_site_access
Read-onlyIdempotent

Check if your API key can access a specific Plausible site by returning today's visitor count, validating credentials and resolving 'not found' or authentication errors.

Instructions

Verify that the configured API key can query a site, and show today's visitor count as a smoke test.

Call this first when a user mentions a new site, or when other tools return authentication or "not found" errors. The Stats API has no "list sites" endpoint (that is the separate Sites API with a different key type), so this checks one site at a time.

Example: {"site_id": "example.com"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
site_idNoSite domain exactly as registered in Plausible, e.g. "example.com". Optional when PLAUSIBLE_DEFAULT_SITE_ID is set.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already signal readOnly, idempotent, and non-destructive behavior. The description adds value by framing it as a smoke test, stating it shows today's visitor count, and disclosing that there is no list-sites endpoint in the Stats API—useful context beyond the annotations.

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?

Four short, purposeful sentences: purpose, when to call, API limitation context, and a concrete example. Every sentence earns its place and no filler is present.

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?

For a simple one-optional-parameter tool with no output schema, the description covers purpose, trigger conditions, limitation, and an example. It names the observable result (today's visitor count), though it does not specify exact output formatting or error signaling, leaving a small gap.

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% and the schema already fully documents site_id's pattern, length, and optionality. The description's example reinforces usage but does not add meaning beyond what the schema already provides, matching the baseline.

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 uses a specific verb and resource: "Verify that the configured API key can query a site, and show today's visitor count as a smoke test." This unambiguously distinguishes it from sibling data-query tools like plausible_get_aggregate or plausible_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 Guidelines5/5

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

It explicitly states when to invoke the tool: "Call this first when a user mentions a new site, or when other tools return authentication or 'not found' errors." It also explains why it checks one site at a time, referencing the separate Sites API absence, leaving no ambiguity about alternatives.

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