Supplement Advisor MCP Server

classify_form

Determine supplement form quality by pasting product or ingredient details, receiving a verdict with absorption percentage and better alternative.

Instructions

Check if a supplement product uses a good or bad form. Paste any product name or ingredient list and get a quality verdict. Example: 'Nature Made Magnesium Oxide 250mg' → verdict: poor, absorption: ~4%, better alternative: glycinate.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "product_text": "<product_text>",
      "category": "<category>"
    },
    "name": "classify_form"
  }
}

Input Schema

Name	Required	Description	Default
`category`	Yes	The supplement category
`product_text`	Yes	The product name, title, or ingredient text to classify

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Aug 7, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the output contract (verdict, absorption, better alternative) and gives a concrete example. However, it does not mention any limitations (e.g., coverage boundaries, reliance on a database) or the meaning of 'good'/'bad' forms, which could be useful but is not critical for basic use.

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 extremely concise, front-loaded with the primary purpose, and includes a helpful example. Every sentence earns its place, with no filler or redundancy.

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?

Given the tool's simplicity (2 params, no output schema), the description sufficiently explains both input and output. It provides the expected verdict format and example, making it complete for an agent to select and invoke the tool correctly.

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 description coverage is 100%, so the baseline is 3. The description does not add detail about the 'category' parameter beyond what the schema already lists, and while it hints at product_text usage via the example, it does not explain how category affects classification. Thus, it provides minimal added value over 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 a specific action ('Check if a supplement product uses a good or bad form') and resource (supplement product), which is distinct from siblings like recommend_supplement or compare_forms. The example further clarifies the tool's unique output, making its purpose unambiguous.

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 provides clear usage instructions ('Paste any product name or ingredient list') and implies when to use the tool (when a quality verdict on a single product's form is needed). However, it does not explicitly compare with or exclude sibling tools, so it lacks an explicit when-not-to-use statement.

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

Deploy Server