Three MCP servers for e-commerce research with Claude: Shopify, Amazon, and Google Maps tools

Three MCP servers for e-commerce research with Claude
A developer created three MCP (Model Context Protocol) servers to help Claude AI pull real competitive data for e-commerce research, eliminating the need for manual copy-pasting or custom code each time.
Key Details
The developer built these tools after wasting approximately 10 hours on manual data gathering before realizing they could automate the process. All three MCP servers are hosted on Apify and can be called directly by Claude.
- Shopify Intel MCP: Lets Claude analyze any public Shopify store without requiring an API key. Examples of queries include "what apps is Gymshark running" or "show me Allbirds' full product catalog with pricing."
- Amazon Intel MCP: Performs product research with a custom scoring system that weights demand signals, competition level, price health, and BSR (Best Sellers Rank). Instead of returning raw results, it scores each product on how good of an opportunity it represents.
- Google Maps Intel MCP: Finds local businesses by industry and location, scoring them as sales leads. It also generates an outreach hint for each business based on data signals that drove the score—for example, "no website, offer web design" or "low rating, offer reputation management."
The MCP servers are live and accessible at:
- https://apify.com/rothy/shopify-intel-mcp
- https://apify.com/rothy/amazon-intel-mcp
- https://apify.com/rothy/gmaps-intel-mcp
The developer is seeking feedback on other data sources that could be useful to add.
📖 Read the full source: r/ClaudeAI
👀 See Also

DebugBase: A Collective Error Knowledge Base for AI Coding Agents via MCP
DebugBase is an MCP-compatible tool that provides a shared knowledge base where AI coding agents can check for known fixes to common errors like Next.js hydration mismatches or TypeScript resolution issues. It includes 11 MCP tools and comes pre-seeded with 58 error/fix pairs from real agent sessions.

Claude-Code v2.1.76 adds MCP elicitation, worktree optimizations, and numerous fixes
Claude-Code v2.1.76 introduces MCP elicitation support for structured input mid-task, adds worktree.sparsePaths for monorepo efficiency, and fixes 20+ issues including deferred tool schema loss, slash command problems, and Remote Control session stability.

LoreConvo: MCP Server Adds Persistent Session Memory to Claude Code
LoreConvo is an MCP server that provides Claude Code with persistent session memory, automatically saving and loading context between sessions. It saves 3,000-8,000 tokens per session by eliminating re-contexting overhead.

Local Qwen Models Achieve Browser Automation with Stepwise Planning and Compact DOM
A developer found small local LLMs like Qwen 8B and 4B succeed at browser automation using stepwise planning instead of upfront multi-step plans, combined with a compact semantic DOM representation that reduces token usage from 50-100K+ to ~15K for full flows.