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jeonghwanko

coffee-price-mcp

by jeonghwanko
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: get_cheapest_coffee ranks top deals based on user memberships, search_coffee_deals provides flexible filtering, and verify_receipt_price checks a given price against current deals. No overlap or ambiguity.

    Naming Consistency5/5

    All tools use the verb_noun pattern in snake_case: get_cheapest_coffee, search_coffee_deals, verify_receipt_price. The convention is perfectly consistent.

    Tool Count4/5

    With 3 tools, the count is slightly low but appropriate for a focused price-checking domain. Each tool earns its place, and expanding to 4-5 would not harm, but the current count is reasonable.

    Completeness4/5

    The tools cover key operations: retrieving cheapest options, searching/filtering deals, and verifying a receipt price. Minor gaps exist, such as lacking a tool to list all brands or deals without filtering, but the core workflows are well-supported.

  • Average 3.9/5 across 3 of 3 tools scored. Lowest: 3.1/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 6 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

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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?

    No annotations exist, so the description carries full burden. It does not disclose read-only behavior, rate limits, or any side effects. The description only states what the tool does, not behavioral traits.

    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 concise sentences that front-load the purpose and key filtering dimensions. No unnecessary words. Every sentence adds value.

    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 complexity (6 optional parameters, no output schema, no annotations), the description covers filtering scope and return value but omits details on pagination, response format, or behavior when multiple filters are combined. It is adequate but leaves gaps.

    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 covers all 6 parameters with descriptions (100% coverage). The description adds the context that effective price is returned, which is not in the schema. However, it doesn't explain parameter interdependencies or constraints beyond what the schema already provides, so baseline 3 is appropriate.

    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?

    Description clearly states it searches/filters coffee deals by brand, carrier/credit card, type, keyword, and today-only. It specifies the return includes effective price. However, it doesn't explicitly differentiate from sibling tools (get_cheapest_coffee, verify_receipt_price), leaving room for confusion.

    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 on when to use this tool vs alternatives. No prerequisites, exclusions, or context about appropriate use cases are provided.

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

  • Behavior4/5

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

    No annotations provided, so description carries full burden. Details ranking logic (net price ascending, only applicable benefits). Does not address authentication or output format, but these are minimal risks.

    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 concise sentences with clear structure. Every word adds value. Front-loaded with purpose.

    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 4 parameters and no output schema, description covers core behavior (ranking, filtering). Lacks output format details but sufficient for simple query. Complete enough for agent to understand.

    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 100% with good descriptions. Description adds ranking context but does not significantly expand beyond schema. Baseline score of 3 appropriate as description adds moderate value.

    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?

    Description clearly states the tool ranks coffee options by cheapest net price given memberships. Verb is implied but specific (rank by cheapest). Differentiates from siblings (search_coffee_deals for broad search, verify_receipt_price for verification).

    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?

    Description implies usage context: when user wants cheapest coffee with available benefits. Does not explicitly state when-not-to-use or compare to alternatives, but sibling names provide contrast. Guideline is clear but lacks explicit exclusion.

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

  • Behavior4/5

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

    With no annotations provided, the description carries full burden. It discloses that the tool is read-only (non-destructive) and provides a judgment and suggestions. However, it does not detail the exact output structure or potential limits, but it is sufficient for a simple check tool.

    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 very concise: two sentences clearly stating the purpose and key behavioral notes. The parenthetical read-only note is efficiently placed. No unnecessary words.

    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?

    Although there is no output schema, the description gives a high-level overview of the return (judgment and better deals). For a simple tool with 3 parameters and a clear function, this is mostly adequate, though more structured output details could help the agent.

    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 coverage is 100% with descriptions for all parameters. The tool description adds context by explaining how parameters are used in the analysis (comparing paid price to regular and lowest). It does not repeat schema details but enhances understanding of the tool's logic.

    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 clearly states the tool's purpose: checking if a paid coffee price is appropriate by comparing against regular and lowest prices, and providing a judgment (great/fair/overpaid) along with better deal suggestions. It distinguishes from sibling tools by explicitly stating it is for price checking, not receipt submission, and is read-only.

    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 implies when to use this tool (when you have a specific paid price to verify) and what to expect (judgment and suggestions). However, it does not explicitly compare to sibling tools like `get_cheapest_coffee` or `search_coffee_deals`, leaving the agent to infer the differentiation.

    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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