Flowsery

Get Visitors by Country

get_countries

Read-only

Get visitor breakdown by country.

Input Schema

TableJSON Schema

Name	Required	Description
`endAt`	No	ISO 8601 end date (e.g. "2026-01-31")
`limit`	No	Max results (1-1000, default: 100)
`domain`	No	Website domain to query. Required when using a workspace token unless websiteId is provided.
`offset`	No	Pagination offset (default: 0)
`startAt`	No	ISO 8601 start date (e.g. "2026-01-01")
`timezone`	No	IANA timezone (e.g. "America/New_York"). Falls back to site default.
`filter_os`	No	Filter by operating system
`websiteId`	No	Website ID to query. Required when using a workspace token unless domain is provided.
`filter_ref`	No	Filter by ref URL parameter
`filter_via`	No	Filter by via URL parameter
`filter_city`	No	Filter by city
`filter_goal`	No	Filter by goal name
`filter_page`	No	Filter by page path
`filter_device`	No	Filter by device type: desktop, mobile, tablet
`filter_region`	No	Filter by region
`filter_source`	No	Filter by source URL parameter
`filter_browser`	No	Filter by browser name
`filter_channel`	No	Filter by marketing channel
`filter_country`	No	Filter by country
`filter_hostname`	No	Filter by hostname
`filter_referrer`	No	Filter by referrer domain
`filter_utm_term`	No	Filter by UTM term
`filter_entry_page`	No	Filter by entry/landing page
`filter_utm_medium`	No	Filter by UTM medium
`filter_utm_source`	No	Filter by UTM source
`filter_utm_content`	No	Filter by UTM content
`filter_utm_campaign`	No	Filter by UTM campaign

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	No	Countries with visitor counts.

Schema Changelog

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

First observedSep 1, 2026

TDQS

C2.9/5.0

Behavior2/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds no further behavioral context such as whether counts are unique visitors, whether a date range is required, or how results are ordered.

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 front-loaded sentence with no filler words. It is concise, though it is arguably minimal given the large parameter set and sibling tool context.

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 simple read-only grouped analytics endpoint, the description plus rich schema, annotations, and output schema is adequate. However, it lacks usage differentiation and does not clarify metric semantics, leaving some contextual gaps for an agent selecting among many similar analytics tools.

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 description coverage is 100%, so all 27 parameters are already documented. The tool description does not add any parameter-level meaning, placing it at the baseline of 3.

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 it returns a visitor breakdown grouped by country, using a specific verb and resource. It is distinguishable from siblings like get_cities and get_regions by the country dimension, though it does not explicitly contrast itself with them.

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?

There is no guidance on when to use this tool versus alternatives such as get_cities, get_regions, or get_breakdown. The description only restates the core purpose and leaves tool selection to inference from the name.

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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TDQS

A3.6/5.0

Disambiguation5/5

Each tool serves a distinct purpose: get_* tools cover different analytics dimensions (browsers, cities, countries, etc.) with clear scopes, while issue management and tracking tools are clearly separated. Even get_breakdown is explicitly scoped to dimensions without dedicated endpoints, avoiding overlap.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with snake_case (delete_goals, get_overview, track_goal, update_issue_status). Verbs are specific and predictable (get, delete, track, list, update), and there are no naming style mixes.

Tool Count2/5

At 27 tools, the set exceeds the 25-tool threshold considered 'too many.' While the domain is broad (analytics, tracking, issues), many get_* tools could be consolidated into get_breakdown with filter parameters, making the count feel inflated rather than necessarily well-scoped.

Completeness4/5

The tool surface covers the full analytics lifecycle: overview, time series, breakdowns, real-time data, visitor profiles, goal/payment tracking and deletion, plus AI issue listing/detail/status updates. Minor gaps exist (e.g., no update for goals/payments, no explicit list of defined goals), but these are non-critical and don't impair typical workflows.

Resources

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