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umami-mcp-server

by arttus
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TypeScript
Remote

Get Umami website details

umami_get_website
Read-onlyIdempotent

Get website configuration details and collected data date range to verify tracking coverage, preventing empty periods from being read as traffic drops.

Instructions

Get configuration details for one website plus the date range of data actually collected for it.

The date range matters: querying a period before tracking started returns zeros, which is easy to misread as a traffic collapse. Check this first when numbers look surprisingly empty.

Args:

  • website (string, optional): Website ID, name, or domain.

  • response_format ('markdown' | 'json'): Output format (default: 'markdown').

Returns: JSON shape: { "id": string, "name": string, "domain": string, "share_id": string | null, "created_at": string, "data_start": string | null, "data_end": string | null, "active_visitors": number }

Examples:

  • "When did we start tracking example.com?" -> website="example.com"

  • "Is anyone on the site right now?" -> website="example.com"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
websiteNoWebsite ID (UUID), name, or domain. Optional if UMAMI_DEFAULT_WEBSITE is set. Use umami_list_websites to discover values.
response_formatNoOutput format: 'markdown' for a readable summary, 'json' for raw structured data.markdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the existing readOnly/idempotent annotations, the description exposes an important behavioral caveat: data_start/data_end determine whether queries return real traffic or zeros, which can be misread as a collapse. It also discloses the return shape, including nullable fields and active_visitors, adding substantive context.

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 well-structured and front-loaded, with a purpose statement, a valuable caveat, concise args, return shape, and examples. Every section earns its place and there is no filler or repetition that hurts usability.

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

Completeness5/5

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

There is no output schema, so the explicit return shape is necessary and provided. The description covers the non-obvious data coverage behavior, defaults, parameter notes, and examples, making it complete enough for an agent to call the tool correctly without external documentation.

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%, and the description mostly restates what the schema already says for 'website' and 'response_format'. The examples add illustrative value but do not introduce new parameter semantics beyond the schema, so the high-coverage baseline of 3 is appropriate.

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 states a specific verb and resource: 'get configuration details for one website' plus the date range of actually collected data. The scope 'one website' distinguishes it from list-style siblings like umami_list_websites, and the focus on configuration/data coverage separates it from stats, sessions, and heatmap tools.

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

Usage Guidelines4/5

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

The description gives clear context on when the tool is useful: 'Check this first when numbers look surprisingly empty' because pre-tracking periods return zeros. It also provides natural-language examples that map to invocations. It does not explicitly name alternative tools or state when-not-to-use, so it does not reach a 5.

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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