Product discovery
Search sourcing candidates, compare safe product fields, and avoid overconfident matches when the product identity is unclear.
Kết nối bằng URL MCP connector được host hoặc file cấu hình cho Codex, Claude Desktop, Antigravity và các MCP client khác. Agent có thể tìm sản phẩm JTLGo, ước tính phí vận chuyển từ Trung Quốc, theo dõi lô hàng, xem chi tiết sản phẩm an toàn và chuyển các trường hợp chưa chắc cho nhân viên thật.
https://jtlgo.com/api/mcp - hãy dùng URL connector được host nếu AI client hỗ trợ hosted MCP. Nếu không, dùng file cấu hình hoặc gói stdio local. MCP means Model Context Protocol. Think of it as a secure connector between your AI assistant and a small set of business tools. Instead of copying data between tabs, you ask the assistant in natural language and it calls the JTLGO tools for product search, China sourcing, freight-rate checks, and shipment tracking.
A normal chat assistant can only answer from context. With MCP, the assistant can call approved JTLGO tools: search products, quote shipping, track shipments, inspect product details, and ask for human support when the answer is risky.
The reference workflow is simple: MCP turns an AI assistant into an operator that can safely use real business tools. For JTLGO, those tools are focused on ecommerce sourcing and China logistics.
Search sourcing candidates, compare safe product fields, and avoid overconfident matches when the product identity is unclear.
Quote China freight routes by country, weight, dimensions, cargo type, and route constraints before a buyer commits.
Track JTLGO parcel, shipment, and order tracking numbers, then summarize the latest carrier scan and exception risk.
Fetch product detail, supplier context, and next-step questions without exposing private backend fields to the AI client.
Route uncertain product matches, restricted cargo, and manual procurement requests to email or WhatsApp support.
search_products for product discovery.quote_shipping_rates for China freight estimates.track_shipment for parcel, shipment, and order tracking timelines.get_product_detail for safe detail lookup.human_handoff for manual support.get_mcp_config for setup verification.This is the kind of natural-language flow the page should teach. The buyer asks once; the agent chooses product search, freight quote, shipment tracking, and human fallback when needed.
First call get_mcp_config. Then call search_products with keyword "wireless earbuds" and limit 3. After that call quote_shipping_rates with countryCode "US" and weight 2. Start with the hosted connector URL. Use config snippets only when the client has no connector form, and use the local package only when the client requires stdio.
Paste the hosted MCP URL into your AI client when it has a connector, remote MCP, or Streamable HTTP setup screen.
If the client has no connector form, copy the hosted JSON or TOML from the matching client tab below.
Download the zip only when your client supports local stdio servers but not hosted connector URLs.
Restart the AI client, call get_mcp_config, then test search_products, quote_shipping_rates, or track_shipment with one simple request.
Similar to the reference tutorial, each client supports two setup patterns: Connector for the fastest hosted setup, and Config file for clients that need manual JSON, TOML, or local stdio fallback.
https://jtlgo.com/api/mcp [mcp_servers.jtlgo-commerce]
url = "https://jtlgo.com/api/mcp" [mcp_servers.jtlgo-commerce]
command = "node"
args = ["/Users/you/Downloads/jtlgo-commerce-mcp/scripts/jtlgo-commerce-mcp.mjs"]
env = { JTLGO_API_BASE_URL = "https://api.jtlgo.com", JTLGO_INTERNAL_TOKEN = "YOUR_JTLGO_INTERNAL_TOKEN", JTLGO_SITE = "jtlgo", JTLGO_RATE_API_URL = "https://api.jtlgo.com/sourcing/explore/shipping", JTLGO_RATE_TIMEOUT_MS = "4000", JTLGO_TRACK_API_URL = "https://api.jtlgo.com/api/logi/order/track/ex", JTLGO_TRACK_TIMEOUT_MS = "7000" } codex mcp add jtlgo-commerce \
--env JTLGO_API_BASE_URL=https://api.jtlgo.com \
--env JTLGO_INTERNAL_TOKEN=YOUR_JTLGO_INTERNAL_TOKEN \
--env JTLGO_SITE=jtlgo \
--env JTLGO_TRACK_API_URL=https://api.jtlgo.com/api/logi/order/track/ex \
-- node "/Users/you/Downloads/jtlgo-commerce-mcp/scripts/jtlgo-commerce-mcp.mjs" https://jtlgo.com/api/mcp {
"mcpServers": {
"jtlgo-commerce": {
"url": "https://jtlgo.com/api/mcp"
}
}
} {
"mcpServers": {
"jtlgo-commerce": {
"command": "node",
"args": [
"/Users/you/Downloads/jtlgo-commerce-mcp/scripts/jtlgo-commerce-mcp.mjs"
],
"env": {
"JTLGO_API_BASE_URL": "https://api.jtlgo.com",
"JTLGO_INTERNAL_TOKEN": "YOUR_JTLGO_INTERNAL_TOKEN",
"JTLGO_SITE": "jtlgo",
"JTLGO_RATE_API_URL": "https://api.jtlgo.com/sourcing/explore/shipping",
"JTLGO_RATE_TIMEOUT_MS": "4000",
"JTLGO_TRACK_API_URL": "https://api.jtlgo.com/api/logi/order/track/ex",
"JTLGO_TRACK_TIMEOUT_MS": "7000"
}
}
}
} https://jtlgo.com/api/mcp {
"mcpServers": {
"jtlgo-commerce": {
"url": "https://jtlgo.com/api/mcp"
}
}
} {
"mcpServers": {
"jtlgo-commerce": {
"command": "node",
"args": [
"/Users/you/Downloads/jtlgo-commerce-mcp/scripts/jtlgo-commerce-mcp.mjs"
],
"env": {
"JTLGO_API_BASE_URL": "https://api.jtlgo.com",
"JTLGO_INTERNAL_TOKEN": "YOUR_JTLGO_INTERNAL_TOKEN",
"JTLGO_SITE": "jtlgo",
"JTLGO_RATE_API_URL": "https://api.jtlgo.com/sourcing/explore/shipping",
"JTLGO_RATE_TIMEOUT_MS": "4000",
"JTLGO_TRACK_API_URL": "https://api.jtlgo.com/api/logi/order/track/ex",
"JTLGO_TRACK_TIMEOUT_MS": "7000"
}
}
}
} https://jtlgo.com/api/mcp {
"mcpServers": {
"jtlgo-commerce": {
"url": "https://jtlgo.com/api/mcp"
}
}
} {
"mcpServers": {
"jtlgo-commerce": {
"command": "node",
"args": [
"/Users/you/Downloads/jtlgo-commerce-mcp/scripts/jtlgo-commerce-mcp.mjs"
],
"env": {
"JTLGO_API_BASE_URL": "https://api.jtlgo.com",
"JTLGO_INTERNAL_TOKEN": "YOUR_JTLGO_INTERNAL_TOKEN",
"JTLGO_SITE": "jtlgo",
"JTLGO_RATE_API_URL": "https://api.jtlgo.com/sourcing/explore/shipping",
"JTLGO_RATE_TIMEOUT_MS": "4000",
"JTLGO_TRACK_API_URL": "https://api.jtlgo.com/api/logi/order/track/ex",
"JTLGO_TRACK_TIMEOUT_MS": "7000"
}
}
}
} Use this fallback in ChatGPT mobile, Gemini mobile, or any AI app that cannot add a custom MCP connector. It does not create live API access; it gives the assistant strict rules, required fields, and safe handoff paths.
You are helping me use JTLGO for China sourcing, shipping rates, and shipment tracking, but this chat does NOT have access to JTLGO MCP tools or live JTLGO APIs.
Rules:
1. Answer in the same language I use.
2. Do not invent live product availability, exact shipping prices, carrier scans, customs rules, or delivery promises.
3. If the product, shipping route, or tracking status is uncertain, clearly say it needs JTLGO manual confirmation.
4. For product sourcing, ask for product name, specs, quantity, target price, destination country, use case, and any supplier/product links or images.
5. For shipping rates, ask for destination country/city, actual weight, package dimensions, cargo type, battery/liquid/magnet/brand status, declared value, and delivery speed preference.
6. For tracking, ask for tracking number, JTLGO order number, carrier if known, destination country, and the last visible tracking event.
7. Use these official next steps when live confirmation is needed:
- Rate quote page: https://jtlgo.com/rate-and-ship/
- Tracking page: https://jtlgo.com/tracking/
- Contact page: https://jtlgo.com/contact-us/
- WhatsApp: +86 139 2810 3300
- Email: sales [at] jtlgo.com
Output format:
- What I can assess from the information provided
- Missing details I need from you
- Safest next action
- A short message I can send to JTLGO support if manual help is needed These are the practical search intents behind the page: AI agents need ecommerce tools, product search APIs, China sourcing workflows, shipping-rate estimates, and parcel tracking without building a custom integration from scratch.
Most MCP setup failures come from four things: Node.js is missing, the server path is wrong, the token is wrong, or the AI client was not restarted after editing config.
Install Node.js 20 or newer, close Terminal/PowerShell, open it again, then run node -v.
Check that the config points to the real file path ending in scripts/jtlgo-commerce-mcp.mjs.
Replace YOUR_JTLGO_INTERNAL_TOKEN with your private token. Do not include extra spaces or quotes unless your client requires them.
Restart the AI client completely. On desktop apps, closing the window is not always enough; quit and reopen the app.
Ask the agent to use clearer product terms, provide a source URL, or call human_handoff for email/WhatsApp help.
Provide country code, actual weight, dimensions, and cargo type. Battery, liquid, oversized, and restricted goods may need manual routing.
Check the tracking number format, carrier, order number, and destination country. If the timeline is still blank, call human_handoff for manual review.
No. It supports a hosted HTTP connector URL and a local stdio package. No Chrome extension is required.
Yes. The easiest path is to paste the connector URL. If your client does not support hosted connectors, use the config file or local package fallback.
The page includes Codex, Claude Desktop, and Antigravity examples. Any client that supports hosted HTTP MCP or local stdio MCP can use one of the two patterns.
Ask the AI client to call get_mcp_config. Then test search_products, quote_shipping_rates, or track_shipment with one simple request.
Yes. Use track_shipment with a JTLGO tracking number, parcel tracking number, or order tracking id. If no confident timeline is found, the tool returns manual support guidance.
Use human support when product identity is uncertain, shipping restrictions may apply, rates look incomplete, or the buyer needs manual procurement confirmation.