untappd-mcp-server

get_user_beer_stats

Aggregate a user's distinct beer history from Untappd into breakdowns by style, brewery, and rating.

Instructions

Aggregate a user's distinct beer history into style, brewery, and rating breakdowns (paginates the API — costs 1 call per 50 beers scanned)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "username": "<username>"
    },
    "name": "get_user_beer_stats"
  }
}

Input Schema

Name	Required	Description	Default
`username`	Yes	Untappd username
`max_pages`	No	Max pages to scan at 50 beers/page (default 10 = 500 beers)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Jul 29, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Discloses pagination behavior (cost per 50 beers scanned) and that it aggregate data. With no annotations provided, the description adequately covers the read-only nature and cost implications. However, it doesn't mention auth requirements or error handling.

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?

Single sentence with 20 words, no fluff. Front-loaded with the core action ('Aggregate a user's distinct beer history'), followed by relevant details in parentheses.

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?

Given no output schema, the description hints at return fields (style, brewery, rating breakdowns). It covers pagination and cost. Missing details like error responses or username validation, but sufficient for a tool with only two simple parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 100% of parameters with descriptions. The description adds value by explaining the pagination cost (1 call per 50 beers), which clarifies the 'max_pages' parameter's impact. It also hints at output structure (breakdowns by style, brewery, rating).

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?

Clearly states the tool aggregates a user's distinct beer history into style, brewery, and rating breakdowns. The verb 'aggregate' and resource 'beer history' are specific, and the description distinguishes from sibling tools like get_user_info or get_user_distinct_beers by focusing on aggregation rather than raw lists.

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?

No explicit when-to-use or when-not-to-use guidance compared to siblings. The description implies usage for aggregated breakdowns, but does not state alternatives or exclusions (e.g., if raw list is needed, use get_user_distinct_beers).

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