ScrapingDog-MCP

flipkart_product

Scrape any Flipkart product page by URL to retrieve structured data including title, pricing, specifications, images, ratings, reviews, and offers.

Instructions

Scrape any Flipkart product page by URL to retrieve title, brand, pricing, specifications, images, customer ratings, reviews, payment options, and available offers. [Credits: 5 API credits per successful request] Notes: Product identity is embedded in the url (the /p/ path segment, e.g. itm909c8202e1864). Returns: { product_results: { title, brand, brand_url, description, price, previous_price, discount, delivery_date, payment_options: { emi_available, cod_available, net_banking }, seller: { name, rating, services: [] }, highlights: [], main_image, images: [], overall_rating, ratings_count, reviews_count, specifications: { : { : value } }, reviews: [ { rating, title, comment, reviewer, helpful_count } ] } }

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": {
      "url": "<url>"
    },
    "name": "flipkart_product"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes	URL of the Flipkart product page to scrape (e.g., https://www.flipkart.com/product/p/itm909c8202e1864).
`html`	No	Return the full HTML of the Flipkart page instead of parsed JSON. (default: false)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 10, 2026

TDQS

A3.9/5.0

Behavior3/5

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

With no annotations, description carries full burden. It mentions credit consumption and notes about URL identity, but does not disclose rate limits, error handling, or behavior for invalid URLs. Some transparency but incomplete.

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?

Description is relatively concise with organized sections (credits, notes, returns). Could be slightly more concise, but this is effective.

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?

Given no annotations or output schema, description provides a detailed return structure and credit info. Lacks error behavior and prerequisites, but is largely complete for a scraping tool.

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

Parameters4/5

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

Schema description coverage is 100% (both parameters described). Description adds value by explaining credit cost and return format, enhancing understanding beyond the schema. Baseline 3, plus extra context.

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?

Description explicitly states it scrapes Flipkart product pages via URL and lists the data retrieved (title, brand, pricing, etc.). It clearly distinguishes from sibling tools like flipkart_search (which searches) and other product scrapers.

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?

Description provides credit cost and notes about URL structure, but does not explicitly state when to use this tool versus alternatives (e.g., flipkart_search for search, or amazon_product for Amazon). No exclusion criteria or context for selection.

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

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