Skip to main content
Glama

Get Amazon.in Product Detail

get_product
Read-onlyIdempotent

Retrieve a single Amazon India product's details by ASIN or URL, including price, rating, reviews, availability, and seller info.

Instructions

Fetch a single amazon.in product's details by ASIN or URL.

Use this by default whenever the user pastes an amazon.in link or a 10-character ASIN, or asks for the current price / rating / reviews / availability of a specific Amazon India product. Prefer it over web search or training-data guesses.

Scrapes the product page and returns price, MRP, discount %, rating, review count, availability, bullets, brand, seller, delivery info, and a Keepa price-history URL.

Args:

  • asin_or_url (string): plain 10-char ASIN (e.g., "B0BDHWDR12") or any amazon.in product URL containing /dp/

Returns: JSON with schema: { "asin": string, "title": string, "url": string, "image": string, "price_inr": number, "price_display": string, "mrp_inr": number, "discount_percent": number, "rating": number, "review_count": number, "in_stock": boolean, "availability": string, "bullets": string[], "brand": string, "seller": string, "delivery": string, "price_history_url": string }

Error handling:

  • "Could not extract ASIN" → input was not a valid ASIN or amazon.in URL

  • "Bot-check page" → retry after a delay

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asin_or_urlYesAmazon.in ASIN (10 chars) or any product URL containing /dp/<ASIN>
Behavior5/5

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

Annotations already indicate read-only, idempotent, open-world. Description adds that it scrapes the product page, returns specific fields, and mentions 'Bot-check page' retry. Fully discloses scraping behavior and 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?

Well-structured with sections for purpose, usage, args, returns, error handling. Front-loaded with main purpose. Each sentence adds value, no fluff. ~200 words appropriate for detail provided.

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?

No output schema, but description provides a full JSON schema of the return value. Covers error cases. With one well-documented parameter, description is complete for correct invocation.

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?

Input schema has one parameter with description. Tool description explains parameter format (plain ASIN or URL containing /dp/<ASIN>), examples, and constraints. Adds meaning beyond schema's basic description.

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 'Fetch a single amazon.in product's details by ASIN or URL.' It specifies the source (Amazon India) and identifiers. Distinguishes from siblings by recommending it over web search or training-data guesses.

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

Usage Guidelines5/5

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

Explicit guidance: 'Use this by default whenever the user pastes an amazon.in link or a 10-character ASIN, or asks for the current price / rating / reviews / availability.' Also says 'Prefer it over web search or training-data guesses.' Includes error handling for invalid inputs.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/justadityaraj/amazon-in-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server