Amazon India Product Research MCP

research_keywords

Identify primary, secondary, long-tail, and related keywords for Amazon India products, including search intent, priority, backend terms, and optimal placement in title, bullets, description, and backend fields.

Instructions

Research Amazon India keywords for a product: primary, secondary, long-tail and related keywords, search intent, keyword priority, backend search terms, and where to place each keyword across title, bullets, description and backend fields.

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_name": "<product_name>"
    },
    "name": "research_keywords"
  }
}

Input Schema

Name	Required	Description	Default
`marketplace`	No		amazon.in
`product_name`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.1Aug 23, 2026

TDQS

A4/5.0

Behavior4/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does well by stating not just the output categories but also the guidance aspect ('where to place each keyword across title, bullets, description, and backend fields'). 'Research' implies a non-mutating action, though it does not explicitly state side-effect behavior or data-source constraints.

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?

One sentence with no wasted words. It front-loads the core action and then packs the entire deliverable scope into a compact, readable enumeration. Redundancy is zero.

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?

For a keyword-research tool with no annotations and an output schema, the description covers the key outputs and even the placement guidance. It is slightly incomplete because it never identifies the obvious alternative context (organic listing keyword research vs. PPC keyword suggestions) or notes how the marketplace parameter affects the output.

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 schema has 0% description coverage, but with only two simple parameters this is a minor risk. The description orients product_name toward the product being researched and the marketplace implicitly through 'Amazon India,' but it does not add syntax, examples, or clarify how marketplace can change the regional scope.

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 states a specific action ('Research'), a clear resource ('Amazon India keywords for a product'), and then enumerates the deliverables. The list of output types separates it from PPC-focused siblings like suggest_ppc_keywords or broader tools like research_product.

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

Usage Guidelines3/5

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

It implies the tool is for product-level keyword research on Amazon India and that the results inform listing content placement. However, it does not explicitly say when to choose this tool over suggest_ppc_keywords, plan_ppc_campaign, or other keyword-adjacent siblings, nor does it state any exclusions.

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