Amazon India Product Research MCP

calculate_revenue

Estimate monthly and annual revenue for an Amazon India listing using units sold, best-seller rank, or 'bought in past month' badge. Add product cost to also get a profit range.

Instructions

Estimate monthly and annual revenue for an Amazon India listing from units sold, a best-seller rank, or Amazon's 'X bought in past month' badge. Supply product_cost to also get monthly and annual profit. Returns a range plus the method used, never a single false-precision number.

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": {
      "price": "<price>"
    },
    "name": "calculate_revenue"
  }
}

Input Schema

Name	Required	Default
`bsr`	No
`price`	Yes
`category`	No	Home & Kitchen
`product_cost`	No
`weight_grams`	No
`units_per_month`	No
`bought_past_month`	No
`fulfillment_method`	No	FBA

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.1Aug 23, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the tool returns a range and the method used, avoiding false precision, and mentions that profit is calculated only when product_cost is supplied. This is transparent about the output and the conditional behavior, though it does not mention any side effects, data sources, or error conditions.

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 concise, consisting of two sentences that clearly state the primary function, the optional profit extension, and the output format. It avoids unnecessary detail and is well-structured, with the main purpose stated first.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description provides a good overview of the tool's functionality and output, enough for an agent to decide whether to invoke it. Since an output schema exists, it need not explain return values in detail, and it already mentions the output type. However, it lacks clarity on parameter usage (especially price) and does not fully differentiate from similar sibling tools, leaving some context gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description covers some parameters (units, BSR, bought past month, product_cost) but omits several others, most notably price (which is the only required parameter) and category, weight_grams, and fulfillment_method. It also uses the ambiguous term 'units' which could refer to either units_per_month or bought_past_month. Schema coverage is 0%, so the description must compensate, but it leaves significant gaps.

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's purpose: it estimates monthly and annual revenue for an Amazon India listing. It specifies the resource (Amazon India listing) and the action (estimate revenue), and distinguishes itself by mentioning the optional profit calculation with product_cost. It also clearly notes the output format, making it distinct from sibling tools like analyze_product_demand or calculate_profitability.

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 implies when to use the tool (when revenue or profit estimation is needed) and lists the input sources (units, BSR, bought past month). However, it does not explicitly contrast with similar sibling tools like calculate_profitability, and it lacks clear conditions or prerequisites. The guidance is adequate but not fully explicit.

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