Amazon India Product Research MCP

plan_ppc_campaign

Create a three-campaign Sponsored Products advertising plan for Amazon India, including budgets, bids, keywords, negatives, forecasts, weekly optimization, and warnings when margin cannot support ads.

Instructions

Build a complete Sponsored Products plan for a product on Amazon India: a three-campaign structure (Auto discovery, Manual Exact core, Phrase/Broad expansion) with the budget split across them, default bids per campaign, keyword assignments, negative keywords, projected clicks / orders / ad sales, a weekly optimisation routine, and warnings when the margin cannot support advertising.

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>",
      "selling_price": "<selling_price>",
      "product_cost": "<product_cost>"
    },
    "name": "plan_ppc_campaign"
  }
}

Input Schema

Name	Required	Default
`category`	No	Home & Kitchen
`target_acos`	No
`launch_phase`	No
`product_cost`	Yes
`product_name`	Yes
`selling_price`	Yes
`conversion_rate`	No
`monthly_ad_budget`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.1Aug 23, 2026

TDQS

A3.5/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal an important behavior: 'warnings when the margin cannot support advertising,' which hints at validation logic. However, it does not mention prerequisites (e.g., product research data), potential side effects (e.g., long-running computation), or handling of invalid inputs (e.g., negative selling price). Adequate but not comprehensive.

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?

The description is one dense sentence that packs in a large amount of crucial detail without filler. It front-loads the core purpose and then lists the plan's contents efficiently. A slightly more structured format (e.g., breaking out the list) could improve skimmability, but the sentence remains clear and earns its length.

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

Completeness3/5

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

Given the tool's complexity (8 parameters) and the existence of an output schema, the description adequately covers the plan's scope but misses input constraints and any preconditions. It does not mention that costs/prices are in INR or that certain parameters have dependencies. An output schema may cover return structure, but parameter semantics and preconditions are not addressed in the description.

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?

Schema description coverage is 0%, so the description must clarify parameter meaning, but it does not. While parameter names like product_name and selling_price are self-explanatory, ambiguous ones like target_acos, conversion_rate (decimal or percentage?), and launch_phase (what behavior changes?) remain undefined. The description lists plan components but fails to map them to the input fields, leaving agents to guess units and formats.

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 clear, specific action: 'Build a complete Sponsored Products plan for a product on Amazon India' and enumerates the plan's components (three-campaign structure, budget split, bids, keywords, projections, optimization routine, warnings). This differentiates it from sibling tools like calculate_ppc_bids (bids only) and suggest_ppc_keywords (keywords only) by covering the full planning scope.

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?

The description implies use when a comprehensive Amazon India Sponsored Products plan is needed, listing many deliverables. However, it never explicitly contrasts with related tools (e.g., calculate_ppc_bids, suggest_ppc_keywords) or states when not to use it, such as when only one component is required. Clear context is present, but exclusions and alternatives are missing.

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