Bar Assistant MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: managing shelf ingredients (add/remove/get), searching for ingredients, listing bars, and getting cocktails from the shelf. The actions and targets are well-defined, making misselection unlikely.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case (e.g., add_ingredients_to_shelf, get_shelf_cocktails). The naming is predictable and readable throughout the set, with no deviations in style.
Tool Count5/5
With 6 tools, this server is well-scoped for a bar assistant domain. Each tool earns its place by covering core operations like ingredient management, cocktail discovery, and bar listing, without being too sparse or bloated.
Completeness4/5
The tool set covers key workflows: CRUD for shelf ingredients (add, remove, get), ingredient search, bar listing, and cocktail generation. A minor gap is the lack of tools for directly managing cocktails or bars (e.g., create/delete bars), but agents can work around this with the provided operations.
Average 3/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool adds ingredients but doesn't cover critical aspects like whether this is a mutating operation, permission requirements, error handling for invalid IDs, or if duplicates are allowed. This leaves significant gaps in understanding the tool's behavior.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized, making it easy to parse while conveying the core action and mechanism.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a mutating operation with no annotations and no output schema, the description is incomplete. It fails to address behavioral traits like side effects, response format, or error conditions, which are crucial for an agent to use this tool effectively in context with its siblings.
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 the input schema fully documents both parameters. The description adds minimal value by mentioning 'by their IDs', which aligns with the schema's 'ingredient_ids' parameter, but doesn't provide additional context like format examples or usage tips beyond what's already in the structured data.
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 the action ('Add ingredients') and the target resource ('to your bar shelf'), with specificity about the mechanism ('by their IDs'). However, it doesn't explicitly distinguish this tool from its sibling 'remove_ingredients_from_shelf' beyond the opposite action, missing an opportunity for clearer differentiation.
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?
No guidance is provided on when to use this tool versus alternatives like 'search_ingredients' for discovery or 'get_shelf_ingredients' for viewing. The description lacks context about prerequisites, such as needing valid ingredient IDs or bar access, leaving usage scenarios implied but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action is 'Remove,' implying a destructive mutation, but does not specify permissions required, whether removal is permanent or reversible, error handling, or rate limits. This is a significant gap for a mutation tool with zero annotation coverage.
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 a single, efficient sentence with zero waste. It is front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place without redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a destructive mutation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, return values, error conditions, and usage context. For a tool that modifies data, this minimal description does not provide enough information for safe and effective use.
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 the schema already documents both parameters ('ingredient_ids' and 'bar_id') with clear descriptions. The description adds no additional meaning beyond what the schema provides, such as format details or usage examples. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Remove') and resource ('ingredients from your bar shelf'), specifying removal by IDs. It distinguishes from siblings like 'add_ingredients_to_shelf' by indicating removal rather than addition, though it doesn't explicitly contrast with other tools. The purpose is specific and actionable.
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?
No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, exclusions, or contextual cues (e.g., use after 'get_shelf_ingredients' to identify IDs). It lacks explicit when/when-not instructions or named alternatives, leaving usage unclear beyond the basic action.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool searches for ingredients by name to find IDs, implying a read-only operation, but doesn't cover aspects like authentication needs, rate limits, error handling, or response format. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and appropriately sized, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a search tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., list of IDs, structured data), potential limitations (e.g., partial matches, case sensitivity), or how the optional 'bar_id' parameter affects results. This leaves the agent with insufficient context for effective use.
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?
The schema description coverage is 100%, with clear descriptions for both parameters ('name' and 'bar_id'). The description adds minimal value beyond the schema, as it only mentions searching by name without elaborating on parameter interactions or usage nuances. This meets the baseline for high schema coverage.
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 the tool's purpose with a specific verb ('search') and resource ('ingredients'), explaining it finds ingredient IDs by name. However, it doesn't explicitly differentiate from sibling tools like 'get_shelf_ingredients' or 'list_bars', which might also involve ingredient-related operations.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_shelf_ingredients' for retrieving ingredients from a shelf or 'list_bars' for bar-related data, leaving the agent to infer usage context without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves cocktails based on shelf ingredients but lacks details on permissions, rate limits, pagination behavior (implied by the 'page' parameter but not explained), or response format. For a read operation with zero annotation coverage, this is a significant gap in transparency.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it easy for an agent to parse quickly. Every part of the sentence earns its place by conveying essential information.
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?
Given the tool's moderate complexity (a read operation with 2 optional parameters) and no annotations or output schema, the description is minimally adequate. It explains what the tool does but lacks behavioral details (e.g., pagination, response structure) and usage context. It meets the bare minimum for a simple tool but doesn't fully compensate for the absence of structured data.
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?
The input schema has 100% description coverage, with clear documentation for both parameters ('bar_id' and 'page'). The description doesn't add any meaning beyond the schema, such as explaining how 'bar_id' relates to 'BAR_ASSISTANT_BAR_ID' or detailing pagination logic. With high schema coverage, the baseline score of 3 is appropriate, as the schema handles parameter semantics adequately.
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 the tool's purpose: 'Get all cocktails you can make with ingredients on your bar shelf.' It specifies the verb ('Get'), resource ('cocktails'), and scope ('with ingredients on your bar shelf'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_shelf_ingredients' or 'search_ingredients,' which prevents a perfect score.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_shelf_ingredients' (which lists ingredients) or 'search_ingredients' (which might find cocktails by ingredient), leaving the agent to infer usage context. There's no explicit when/when-not or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states the tool retrieves data ('Get'), implying it's a read operation, but doesn't mention pagination behavior, rate limits, authentication needs, or error handling. This leaves significant gaps for a tool with parameters.
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 a single, efficient sentence with no wasted words, clearly front-loading the purpose. Every part earns its place by specifying action, resource, scope, and detail level.
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?
Given no annotations, no output schema, and 2 parameters with full schema coverage, the description is minimally adequate. It covers the basic purpose but lacks behavioral details and usage guidance, making it incomplete for optimal agent use without additional context.
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 the schema already documents both parameters. The description adds no additional meaning beyond implying retrieval of 'all' ingredients, which doesn't clarify parameter usage like pagination or bar_id context. Baseline 3 is appropriate as the schema handles parameter documentation.
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 the action ('Get') and resource ('ingredients currently on your bar shelf'), specifying scope ('all') and detail level ('detailed information'). It doesn't explicitly differentiate from sibling tools like 'search_ingredients' or 'get_shelf_cocktails', which would require a 5.
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?
No guidance is provided on when to use this tool versus alternatives like 'search_ingredients' or 'get_shelf_cocktails', nor are prerequisites or exclusions mentioned. The description implies usage for retrieving shelf ingredients but lacks explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It states the tool lists bars and retrieves IDs, implying a read-only operation, but doesn't clarify if it requires authentication, has rate limits, returns paginated results, or includes metadata like bar names or statuses. This leaves gaps in understanding the tool's operational traits.
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, clear sentence that efficiently conveys the tool's purpose without unnecessary words. It's front-loaded with the main action and resource, making it easy to parse. However, it could be slightly more structured by explicitly stating it's a read operation or adding brief context, but it's still highly concise.
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?
Given the tool has 0 parameters, no annotations, and no output schema, the description is minimally adequate. It explains what the tool does but lacks details on behavior, output format, or usage context. For a simple list tool, this might suffice, but without annotations or output schema, more guidance on what 'IDs' entail or how results are structured would improve completeness.
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?
The input schema has 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description doesn't mention any parameters, which is appropriate here since none are required. This aligns with the schema, so it earns a baseline score of 4 for not introducing confusion or omissions.
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 the action ('List all bars') and the resource ('bars'), specifying that it retrieves bars the user has access to along with their IDs. However, it doesn't differentiate this tool from potential siblings like 'search_ingredients' or 'get_shelf_ingredients', which might also list resources but with different scopes or filters.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, such as authentication or context needed, nor does it specify if this is for initial setup, inventory checks, or other scenarios. Without such context, the agent might misuse it or overlook better-suited tools.
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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