plausible_list_sitesList the sites the API key can access (domain + timezone), with cursor pagination. Requires an enterprise plan. Plausible: GET /api/v1/sites.
| Name | Required | Description | Default |
|---|---|---|---|
| after | No | Cursor for the next page (from meta.after). | |
| limit | No | Sites per page. | |
| before | No | Cursor for the previous page (from meta.before). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint annotation, the description adds behavioral context by mentioning the enterprise plan requirement and the cursor pagination approach. No contradictions with annotations; readOnlyHint aligns with a list operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary purpose, and includes the endpoint reference. Every sentence adds value with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no output schema, the description provides adequate context: accessible sites, returned fields, pagination, and plan requirement. It lacks explicit error/edge-case info, but annotations and schema cover the basics well.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with parameter descriptions for after, before, and limit. The description adds general pagination context but does not provide additional parameter-level semantics beyond what the schema already states.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies a specific action ('List'), a resource ('sites the API key can access'), and provides detail on what is returned ('domain + timezone'). It clearly distinguishes from sibling tools like get_site, which targets a single site.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states a key prerequisite ('Requires an enterprise plan') and mentions cursor pagination, giving clear context for when this tool is applicable. However, it does not explicitly mention alternatives or when not to use it, so it misses the explicit exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.