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valetdotdev

recipe-mcp

by valetdotdev
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TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.3

  • Disambiguation5/5

    generate_recipe creates a new recipe, while transform_recipe modifies an existing one. The semantic boundary is clear, with no overlap in purpose.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern: generate_recipe and transform_recipe. The verbs are distinct and the object is uniform.

    Tool Count3/5

    With only two tools, the server feels thin for a recipe domain. While the scope could be narrowly focused on generation, the count is borderline.

    Completeness2/5

    transform_recipe requires an existing recipe, but there is no tool to retrieve or list recipes. This is a significant gap that leaves agents unable to obtain the input needed for transformation.

  • Average 3.5/5 across 2 of 2 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

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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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 are provided, so the description must disclose behavioral traits. It states 'transform' but does not clarify whether the original recipe is modified, a new one is returned, or how unspecified fields are handled. This is a significant gap.

    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 sentence, front-loaded with the core action, and includes useful examples without unnecessary detail.

    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?

    With a complex nested recipe schema and no output schema, the description should explain what the transformed result looks like or whether original fields are preserved. The absence of return behavior leaves the tool incomplete.

    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 100%, so descriptions for all parameters are already present. The tool description adds a few examples but no additional meaning beyond what the schema provides. Baseline 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 clearly states the tool transforms an existing recipe using instructions, with concrete examples (vegan, calories, servings). This distinguishes it from the sibling tool generate_recipe, which creates new recipes.

    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?

    The description implies use when you have an existing recipe to modify, and examples show typical scenarios. However, it does not explicitly mention when not to use it or compare against generate_recipe.

    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 behavioral traits. It only states the tool generates a recipe, without mentioning return format, dependencies, side effects, or error conditions. This is a significant transparency gap.

    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 concise sentence that clearly states the tool's function. No wasted words.

    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?

    With no output schema and no annotations, the description should provide more context about return values and limitations. It only states the tool generates a recipe, leaving the agent unaware of output structure and other behavioral details. The sibling tool adds a need for distinguishing guidance, which is absent.

    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 provides complete descriptions for all 7 parameters, so the description doesn't need to explain them. The description's mention of 'natural language instructions and dietary preferences' adds a high-level summary but no additional semantics beyond the schema.

    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 generates a new recipe, using a specific verb and resource. It distinguishes from the sibling 'transform_recipe' by implying creation rather than modification.

    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 clearly indicates the tool is for generating new recipes from user preferences, providing clear usage context. It does not explicitly mention alternatives or exclusions, but the sibling name 'transform_recipe' helps distinguish, so no explicit guidance is required.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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