A
licenseA
qualityD
maintenanceEnables natural language access to USDA's FoodData Central database with 1M+ foods, supporting search, nutrition facts, food comparison, and daily value calculations.
8
MIT
kcaldata
Server Details
Natural-language calorie lookup. Send '2 large eggs', get USDA-sourced nutrition data.
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- Status
- Healthy
- Uptime
- 100.0% over 37 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
- Repository
- kcaldata/kcaldata
- GitHub Stars
- 0
TDQS
A4.4/5.0
Scored across 1 tool
Disambiguation5/5
With only one tool, there is no risk of choosing the wrong tool or confusing overlapping purposes. `lookup_calories` has a clear, focused responsibility, making the tool surface completely unambiguous.
Naming Consistency5/5
The sole tool name `lookup_calories` follows a clear snake_case verb_noun pattern. There are no other names to conflict with it, but the naming style used is clean and descriptive.
Tool Count3/5
The single tool is focused and performs a real service, but one tool feels thin for an MCP server. While the scope may be intentionally small, a calorie data server would often benefit from companion tools like food search or lookup alternatives, making the count borderline.
Completeness4/5
For the stated purpose of calorie lookup, the tool covers the core workflow well: it accepts natural-language food descriptions, calculates calories, and explains the calculation. There are no CRUD requirements in this read-only lookup domain, though there is no built-in handling for ambiguous matches or multi-food batch operations, which is a minor gap.
Available Tools
1 toollookup_caloriesAInspect
Look up calorie information for a food or meal.
Accepts natural-language descriptions including quantity and unit, e.g. "2 large eggs", "8 oz salmon", "1 cup rice", "3 slices bacon", or a plain food name like "banana". Returns the matched food, its calories, the total for the amount given, and how it was calculated.
Free tier: 100 calls/day. Beyond that, pay $0.005 USDC per call (x402).
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
TDQS
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description discloses rate limits (100 calls/day) and payment model, as well as what the tool returns (matched food, calories, total, calculation). This is sufficient behavioral context.
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?
Five sentences, front-loaded with purpose, clear structure. Could be slightly more concise, but no extraneous information. Effective and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema or siblings, the description covers purpose, usage examples, behavioral traits, and cost. Complete and adequate for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter 'query' with no schema description, but the tool description thoroughly explains its use: accepts natural-language descriptions with examples. This adds significant meaning beyond the bare schema type.
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 it looks up calorie information for a food or meal, with a specific verb and resource. It distinguishes itself by accepting natural-language descriptions, which is unique and clear.
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?
Provides examples of natural-language queries and mentions the free tier and payment model. No sibling tools exist, so no alternative guidance needed, but it gives enough context for appropriate use.
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 tool update
- First observed
lookup_calories
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