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Nutrition By Api Ninjas MCP Server

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Nutrition By Api Ninjas MCP Server

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用于访问 Nutrition By Api Ninjas API 的 MCP 服务器。

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Related MCP server: Food Data Central MCP Server

简介

这是一个 MCP 服务器，用于访问 Nutrition By Api Ninjas API。

  • PyPI 包名: bach-nutrition_by_api_ninjas

  • 版本: 1.0.0

  • 传输协议: stdio

安装

从 PyPI 安装:

pip install bach-nutrition_by_api_ninjas

从源码安装:

pip install -e .

运行

方式 1: 使用 uvx（推荐，无需安装）

# 运行（uvx 会自动安装并运行）
uvx --from bach-nutrition_by_api_ninjas bach_nutrition_by_api_ninjas

# 或指定版本
uvx --from bach-nutrition_by_api_ninjas@latest bach_nutrition_by_api_ninjas

方式 2: 直接运行（开发模式）

python server.py

方式 3: 安装后作为命令运行

# 安装
pip install bach-nutrition_by_api_ninjas

# 运行（命令名使用下划线）
bach_nutrition_by_api_ninjas

配置

API 认证

此 API 需要认证。请设置环境变量:

export API_KEY="your_api_key_here"

环境变量

变量名

说明

必需

API_KEY

API 密钥

是

PORT

不适用

否

HOST

不适用

否

在 Cursor 中使用

编辑 Cursor MCP 配置文件 ~/.cursor/mcp.json:

{
  "mcpServers": {
    "bach-nutrition_by_api_ninjas": {
      "command": "uvx",
      "args": ["--from", "bach-nutrition_by_api_ninjas", "bach_nutrition_by_api_ninjas"],
      "env": {
        "API_KEY": "your_api_key_here"
      }
    }
  }
}

在 Claude Desktop 中使用

编辑 Claude Desktop 配置文件 claude_desktop_config.json:

{
  "mcpServers": {
    "bach-nutrition_by_api_ninjas": {
      "command": "uvx",
      "args": ["--from", "bach-nutrition_by_api_ninjas", "bach_nutrition_by_api_ninjas"],
      "env": {
        "API_KEY": "your_api_key_here"
      }
    }
  }
}

可用工具

此服务器提供以下工具:

v1nutrition

API Ninjas Nutrition API endpoint.

端点: GET /v1/nutrition

参数:

  • query (string) 必需: Query text to extract nutrition information (e.g. bacon and 3 eggs).

技术栈

  • 传输协议: stdio

  • HTTP 客户端: httpx

许可证

MIT License - 详见 LICENSE 文件。

开发

此服务器由 API-to-MCP 工具生成。

版本: 1.0.0

Available Tools

1 tool
v1nutritionD

API Ninjas Nutrition API endpoint.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesQuery text to extract nutrition information (e.g. bacon and 3 eggs).

TDQS

D1.8/5.0
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.

Tool Schema Changelog

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

  1. 1 tool updatev1.0.0
    • First observedv1nutrition
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

C2.3/5.0

Scored across 1 tool

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.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Related MCP Connectors

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