v0.1.0

First public release. An MCP server that turns Claude Desktop into a product research
assistant for beginner Amazon India sellers — 24 tools, working with zero API keys.

Added

Core research (8 tools)

• research_product — full opportunity report with a weighted 0–100 score
• analyze_product_demand — demand level, trend, seasonality and a launch decision
• analyze_competition — competition level, review barrier, brand dominance, gaps
• calculate_profitability — referral, closing, fulfilment and GST fees, return
  reserve, margin, ROI, break-even and recommended price
• search_suppliers — sourcing research for Parrys, Chennai, Tamil Nadu and India
• analyze_reviews — complaints clustered by theme with supplier-level fixes
• research_keywords — primary, secondary, long-tail and backend search terms
• generate_listing — title, bullets, description, image brief and compliance checks

Sales and competitor intelligence (6 tools)

• calculate_revenue — revenue from units, BSR curves or purchase badges, as a range
• analyze_competitors — per-competitor units, revenue and market share; flags new
  sellers by review count and who clears 300+ units a month
• analyze_purchase_signals — aggregates Amazon's own "bought in past month" badges
• analyze_review_metrics — the review barrier and which listings are beatable
• analyze_evergreen — evergreen vs seasonal scoring from up to 5 years of interest
• analyze_product_images — gallery coverage and a seven-slot image plan

Planning (2 tools)

• find_product_opportunities — screen and rank up to 15 ideas at once
• plan_product_launch — order quantity, budget split, reorder point, payback, timeline

Amazon Ads (3 tools)

• suggest_ppc_keywords — keywords with match type, bid and campaign placement
• calculate_ppc_bids — break-even ACOS and CPC, bid ladder, per-order economics
• plan_ppc_campaign — three-campaign structure, budget split, weekly routine

Live data (5 tools)

• search_web — DuckDuckGo (free, no key), Brave, Serper, Tavily, Google CSE
• scrape_amazon_search — live search results with purchase badges
• scrape_amazon_product — product page with BSR, weight and sales estimate
• scrape_listing_details — full listing teardown, graded 0–100
• scraper_status — what the live-data layer is configured to do

Free live data sources, no API keys

• Google Trends via pytrends for real India search interest and seasonality
• DuckDuckGo web search
• Public amazon.in pages through a guardrailed scraping layer

Data integrity

• Every meaningful output carries source, data_type, confidence and
  last_updated, where data_type is Live, Verified, Estimated, Historical or Demo
• Unparseable values return null, never 0 or a guess
• Modelled figures return a range and name the method that produced them
• Supplier names, prices and MOQs are never fabricated
• Demo mode is deterministic and always labelled

Security

• SSRF protection: scheme, port and resolved IP validated; every redirect hop
  revalidated; loopback, private, link-local and cloud metadata ranges refused
• Credential redaction filter covering library logging such as httpx request URLs
• Prompt-injection scanning and sanitisation of all scraped and searched content,
  surfaced through a content_safety block
• 8 MB response cap, 5-hop redirect limit, validated config file paths

Scraping guardrails

• Domain allowlist, robots.txt enforcement, per-host crawl delay and page budget
• Bot challenges are detected and stop the run; bypass is deliberately not implemented
• Per-field parse coverage reporting, and selector overrides via configuration

Project

• MIT licence, contribution guide, code of conduct and security policy
• CI on Python 3.11, 3.12 and 3.13, plus a security job
• Documentation: setup guide, scraping guide and a 56-prompt library

Known limitations

• BSR-to-units curves and PPC conversion benchmarks are reasoned approximations, not
  calibrated against real sales data. They are labelled Estimated and return ranges.
• The bundled Amazon fee schedule is approximate. Point AMAZON_FEE_CONFIG_PATH at
  your Seller Central rate card for accurate profit figures.
• GST is applied to Amazon's fees but not to the sale price. Since Amazon India prices
  are GST-inclusive, reported margins are optimistic for GST-registered sellers. This
  is the first thing being fixed in 0.2.0.
• Amazon serves bot challenges intermittently, so direct scraping is opportunistic.
  Google Trends and DuckDuckGo are the dependable free sources.
• SP-API and Product Advertising API providers are routed but not implemented; they
  raise a clear error rather than returning fabricated data.

What's Changed

• feat: add live data sources and 12 advanced seller research tools by @Suriya-Ravichandran in #1
• Feat/live data and advanced research tools by @Suriya-Ravichandran in #2
• feat(security): add SSRF protection, credential redaction and injecti… by @Suriya-Ravichandran in #3

New Contributors

• @Suriya-Ravichandran made their first contribution in #1

Full Changelog: https://github.com/Suriya-Ravichandran/amazon-india-seller-mcp/commits/v0.1.0