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BACH-AI-Tools

Nutrition By Api Ninjas MCP Server

by BACH-AI-Tools
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'v1nutrition' has a clearly distinct purpose, as there are no other tools to compare it against.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect. There are no other tools to deviate from any pattern, so it cannot be inconsistent.

    Tool Count2/5

    A single tool for a nutrition API server feels thin and under-scoped. Typically, such a domain would benefit from multiple tools for different operations like searching foods, calculating nutrients, or retrieving dietary information, making this count inappropriate for the apparent scope.

    Completeness1/5

    The tool set is severely incomplete for a nutrition domain. With only one generic endpoint tool, there are significant gaps in coverage, such as missing specific queries for food items, nutrient breakdowns, or meal planning functions, which will likely cause agent failures in handling nutrition-related tasks.

  • Average 1.8/5 across 1 of 1 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 is passing

  • 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

  • Behavior1/5

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

    With no annotations provided, the description carries the full burden of disclosing behavior but fails entirely. It does not mention what data is returned (calories, macros, serving sizes), rate limits, or whether the operation is idempotent.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness2/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    While brief (six words), this represents under-specification rather than effective conciseness. The single sentence fails to earn its place by providing actionable information beyond the tool's identifier.

    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?

    Despite being a single-parameter tool, the description is inadequate. It lacks any indication of return values, output structure, or behavioral side effects, forcing reliance solely on the parameter schema for 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?

    The description adds no parameter information, but the input schema has 100% description coverage (the 'query' parameter is fully documented with an example). Per guidelines, with high schema coverage, the baseline is 3 even when the description is silent on parameters.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose2/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description 'API Ninjas Nutrition API endpoint' merely restates the tool name (v1nutrition) and identifies the domain, functioning as a tautology. It fails to specify what the tool actually does (e.g., extract nutrition facts, calculate calories) or what resource it operates on.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines1/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    No guidance provided on when to use this tool versus alternatives, prerequisites for use (e.g., query format), or when it might be inappropriate. The description is purely nominal.

    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 there are no obvious security issues.
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