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MixWise

Server Details

Cocktails you can make from bottles you already have, full recipes, and the best next bottle to add.

Ownership verified
Status
Healthy
Last Tested
Transport
Streamable HTTP ยท MCP 2025-11-25
URL

TDQS

A4.1/5.0

Scored across 3 tools

Disambiguation5/5

Each tool targets a clearly distinct intent: discovering makeable cocktails from ingredients, retrieving a specific recipe by name, and recommending a single bottle to add. The descriptions reinforce these boundaries with no overlap.

Naming Consistency5/5

All three names follow a consistent snake_case verb_noun pattern (find_cocktails_from_bottles, get_cocktail_recipe, suggest_next_ingredient), and the verbs accurately telegraph each tool's action.

Tool Count4/5

Three tools is on the lean side but well-matched to a focused cocktail-recipe domain where each tool earns its place. Slightly thin, though not a mismatch.

Completeness4/5

The set covers the core journeys of 'what can I make', 'how do I make it', and 'what should I add next'. Minor gaps exist (e.g., searching by name or browsing the catalog), but agents can work around them.

Available Tools

3 tools
find_cocktails_from_bottlesFind cocktails from your bottlesA
Read-only
Inspect

Use this when the user lists bottles or ingredients they have and wants catalog cocktails they can make now, or that are one or two ingredients away. Returns only MixWise catalog recipes. Set zero_proof_only when the user wants drinks without alcohol.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNo
ingredientsYesGeneric ingredient names the user has, for example gin, Campari, sweet vermouth.
max_missingNoHow many missing ingredients still count as almost there. 0 returns ready drinks only.
zero_proof_onlyNoWhen true, return only zero-proof catalog drinks.

Output Schema

ParametersJSON Schema
NameRequiredDescription
linksYes
readyYes
countsYes
recognizedYes
almost_thereYes
unrecognizedYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), so the bar is lower. The description adds real behavior beyond that: results are restricted to catalog recipes and the result set spans ready drinks plus one/two-ingredients-away matches, which tells the agent what kind of output to expect. It stops short of noting limits or ordering/pagination, but the output schema covers returns.

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?

Three short sentences, front-loaded with the usage trigger, followed by scope and the one parameter worth calling out. No filler or restated name/title content.

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?

With an output schema present, return-value detail is not required, and the description covers the activation trigger, result scope, and the zero-proof mode. The one gap is that it doesn't clarify the relationship to suggest_next_ingredient for users who are close but not one-or-two away.

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 75% and the schema already documents zero_proof_only and max_missing. The description only echoes those meanings ('one or two ingredients away', zero-proof case) without adding syntax, defaults, or edge-case guidance beyond the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb+resource: find catalog cocktails from a list of bottles/ingredients the user has. It also bounds the scope to 'MixWise catalog recipes' and the one-or-two-ingredients-away case, which cleanly separates it from get_cocktail_recipe (single recipe lookup) and suggest_next_ingredient (gap filling).

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?

Gives an explicit trigger ('when the user lists bottles or ingredients they have and wants cocktails they can make now'). It also narrows scope to catalog recipes and flags the zero_proof_only scenario, but it never names the sibling tools or states when NOT to use this one versus suggest_next_ingredient.

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

get_cocktail_recipeGet a cocktail recipeA
Read-only
Inspect

Use this when the user asks how to make a specific cocktail by name, or picks one from MixWise results. Returns the full catalog recipe, including measures and steps.

ParametersJSON Schema
NameRequiredDescriptionDefault
slug_or_nameYesCocktail slug or name, for example margarita.

Output Schema

ParametersJSON Schema
NameRequiredDescription
nameNo
slugNo
foundYes
linksYes
garnishNo
glasswareNo
image_urlNo
techniqueNo
difficultyNo
ingredientsNo
suggestionsNo
is_zero_proofNo
responsible_noteNo
short_descriptionNo
instructions_stepsNo

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false, destructiveHint=false, so the safe-read profile is covered. The description adds that it returns the 'full catalog recipe, including measures and steps,' but with an output schema present this is largely duplicative. No rate limits, auth, or not-found behavior are disclosed.

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?

Two tightly written sentences; the usage trigger is front-loaded and the return content follows with zero filler.

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?

With a single required param, an output schema, and annotations covering the safety profile, the description supplies the key trigger context. It could be more complete by clarifying name-vs-slug resolution or fallback behavior when no match is found.

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 single 'slug_or_name' parameter is fully documented in the schema, including an example. The description adds no syntax, slug-format, or matching guidance beyond that, so the baseline of 3 applies.

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 states a specific verb+resource: retrieve the full recipe for one cocktail by name. It implicitly separates itself from sibling discovery tools (find_cocktails_from_bottles, suggest_next_ingredient) by scoping to a single known cocktail, but never names those alternatives explicitly.

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?

"Use this when the user asks how to make a specific cocktail by name, or picks one from MixWise results" gives a clear triggering condition. No explicit when-not or named alternative is provided, so it falls short of a 5.

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

suggest_next_ingredientSuggest the next ingredientA
Read-only
Inspect

Use this when the user asks which single ingredient or bottle to add to unlock the most new cocktails from what they already have. Returns the one catalog bottle that unlocks the most drinks. Set zero_proof_only when the user wants drinks without alcohol. It does not sell anything or link to a store.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoHow many bottles to return. Defaults to the single best one.
ingredientsYes
zero_proof_onlyNoWhen true, only count zero-proof catalog drinks.

Output Schema

ParametersJSON Schema
NameRequiredDescription
linksYes
recognizedYes
suggestionsYes
unrecognizedYes

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly/destructive/openWorld profile, so the bar is lower. The description still adds real context: results come only from the catalog, exactly one bottle is returned by default (matching limit=1), and the 'does not sell anything or link to a store' boundary preempts a plausible user misconception.

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?

Three tight sentences: usage trigger first, then the return semantics, then the modifier flag and the non-commerce boundary. No filler, every sentence carries information an agent needs.

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?

An output schema exists, so return values need not be explained. Given the read-only, single-lookup nature and the schema's own field descriptions, the description supplies everything else needed to call this correctly: when to use it, what it returns in scope terms, and how the zero-proof flag maps to intent.

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?

Coverage is 67%: limit and zero_proof_only have schema descriptions, but the required ingredients array is undocumented in the schema. The description partly compensates by framing inputs as 'what they already have' and maps zero_proof_only to the user's no-alcohol intent, but it never explains the ingredients list format or the limit cap of 5.

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 states a specific verb+resource: it returns the single catalog bottle that unlocks the most new drinks, which is a clear and distinctive purpose. It implicitly distinguishes itself from find_cocktails_from_bottles (listing what you can make now) by focusing on the *next* bottle to add, but never names the siblings, so differentiation is inferential rather than explicit.

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?

Gives a concrete trigger: 'when the user asks which single ingredient or bottle to add to unlock the most new cocktails from what they already have,' plus a conditional for zero-proof requests. However it offers no when-not guidance or named alternatives for cases where the user wants a full list or a recipe instead.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 3 tool updates
    • First observedfind_cocktails_from_bottles
    • First observedget_cocktail_recipe
    • First observedsuggest_next_ingredient

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