Sorftime Seller Agent

Sorftime Seller Agent

> Turn any AI agent into your personal marketplace intelligence analyst. > > Agent-agnostic, MCP-native design. Works with Claude Code, Codex, Cursor, OpenClaw, Hermes, Pi — any MCP-compatible AI agent. > Instant access to 86 marketplace analysis tools. Amazon · Walmart · TikTok Shop · 1688 · Shopee · TEMU. > > No dashboards. No exports. Just talk to your AI.

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⚡ Quick Start

1. Get a free Sorftime account

Visit open-intl.sorftime.com — sign up with Google, free trial credits included. Payment via PayPal when you need more.

2. Install the skill

git clone https://github.com/DannylydST/sorftime-seller-agent.git
cd sorftime-seller-agent
python3 scripts/install.py

3. Ask your AI

"Find blue ocean products in yoga mats on Amazon US for a beginner"
"Analyze this competitor: ASIN B08N5WRWNW"
"Calculate my profit: price $29.99, cost $8.50, weight 1.2lb"

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🤔 Why This Exists

Amazon sellers spend $29–$229/month on marketplace research tools. You log into dashboards, click through menus, export CSV files, then switch to another tool for analysis.

Sorftime Seller Agent skips all that. You talk to your AI assistant — any MCP-compatible agent — and it queries marketplace data directly, analyzes it with a framework of 20 proprietary methodology cards, and gives you actionable insights.

Before: Log in → navigate → click → export → analyze manually  (15–30 min)
After:  "Find blue ocean yoga mat products" → results in 20 seconds

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🧠 What It Can Do

| | Capability | What You Say | |-----|-----------|--------------| | 🔍 | Product Discovery | "Find blue ocean kitchen products under $30" | | 🎯 | Competitor Intelligence | "Break down ASIN B08N5WRWNW — traffic, keywords, pricing" | | 🔑 | Keyword Strategy | "What are the best long-tail keywords for yoga mats?" | | 💰 | Profit Analysis | "Calculate seller profit: $29.99 price, $8.50 cost, 1.2lb" | | 📊 | Market Intelligence | "Analyze the blender category — monopoly, trends, gaps" | | 📈 | Automated Monitoring | "Watch this product and alert me when the price drops" |

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🤖 Agent-Friendly by Design

This skill is built as an agent-agnostic MCP-native skill from the ground up. It's not a Claude Code plugin. It's not a wrapper around an API. It's a self-contained MCP bridge + intelligence layer that any MCP-compatible AI agent can load and use immediately.

| Agent / IDE | How It Works | Setup | |-------------|-------------|-------| | Claude Code | mcporter auto-detection, one-command install | You: "Find blue ocean products in kitchen storage on Amazon US. I'm a beginner seller with $5K budget." > > Agent: [Scans Hidden Profit Index, filters by low competition, beginner-friendly categories] > "Here are 5 opportunities with low brand concentration, 100 reviews."

Analyze a competitor

> You: "Analyze ASIN B08N5WRWNW — give me their traffic keywords and pricing strategy." > > Agent: [Pulls ProductDetail, TrafficTerms, CompetitorKeywords] > "Gaiam Yoga Block — 40K monthly sales, 4.7 stars, $18.99. Top 3 traffic keywords: 'yoga block' (52K), 'yoga blocks 2 pack' (28K), 'cork yoga block' (15K). FBA fee: $12.82. Threat assessment: medium."

Calculate profitability

> You: "I'm sourcing yoga mats at $8.50/piece. I want to sell at $29.99, weight 1.2lb. Should I?" > > Agent: [Runs Calculator with FBA fee estimate] > "Gross margin: 38%. Break-even: 9 units/day. Return rate sensitivity: profit stays positive up to 12% returns. Verdict: viable — proceed."

Research keywords

> You: "What keywords should I target for a new yoga mat listing?" > > Agent: [KeywordDetail, KeywordExtends, KeywordSearchResults] > "Top opportunities: 'extra thick yoga mat' (147K searches, low competition), 'non slip yoga mat' (98K), 'yoga mat with strap' (52K). Avoid 'yoga mat' (1.4M searches, saturated — dominated by Amazon Basics and Gaiam)."

Cross-platform arbitrage

> You: "Are there products selling higher on Walmart than Amazon?" > > Agent: [Cross-platform gap analysis using Sorftime dual-platform data] > "Found 3 products with significant price gaps. 'Premium Yoga Block Set' — $34.99 on Walmart vs $24.99 on Amazon (40% premium). Only 3 sellers on Walmart vs 12 on Amazon."

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🌍 Supported Platforms

| Platform | Data Available | Coverage | |----------|---------------|----------| | Amazon | Products · Keywords · Categories · Reviews · Traffic · Trends · Profit | 14 sites | | Walmart | Products · Keywords · Categories · Traffic · Trends · Variations | US | | TikTok Shop | Products · Categories · Authors · Videos · Trends | US | | Shopee | Products · Keywords · Categories · Shops · Trends | Multi-region | | TEMU | Products · Categories · Shops · Trends | Multi-region | | 1688 | Products · Variations · Similar items | CN |

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🙋 FAQ

Q: Is this official Sorftime? Yes. Built by @DannylydST at Sorftime Data Technology. The skill connects to Sorftime's official MCP API (open-intl.sorftime.com).

Q: Do I need to pay? New accounts get free trial credits. Paid plans available via PayPal when you need more.

Q: What AI tools work with this? Any MCP-compatible agent — Claude Code, Codex (OpenAI), Cursor, OpenClaw, Hermes, Pi, and more. If your AI speaks MCP, it can use Sorftime. The install.py script auto-detects your environment.

Q: How do I get my MCP Key? Sign up at open-intl.sorftime.com → MCP page → copy Key.

Q: Can I use this without an AI agent? Yes — you can call the CLI tools directly: python3 scripts/picker.py --keyword "yoga mat". But the full power comes from AI-driven analysis with the 20 methodology cards.

Q: What's included in the 20 methodology cards? Proprietary analysis frameworks like Hidden Profit Index, Blue Ocean Finder, Competitor Deep-Dive, Keyword Strategy — full-ranking models that show you everything (no hard thresholds that hide borderline products). See references/methodology-cards/.

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📄 License

MIT © DannylydST · Sorftime Data Technology

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Built for sellers. By sellers.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: DannylydST
• Source: DannylydST/sorftime-seller-agent
• License: MIT

Install and usage instructions live in the source repository linked above.