# 1688 Supplier & Factory Finder (`quanmatrix/1688-supplier-sourcing-intelligence`) Actor Search 1688 supplier listings by product query and return supplier, factory, price and sales signals for sourcing shortlists, competitor checks and repeat-run supplier monitoring. - **URL**: https://apify.com/quanmatrix/1688-supplier-sourcing-intelligence.md - **Developed by:** [Rafael Barreto Haddad](https://apify.com/quanmatrix) (community) - **Categories:** E-commerce, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.20 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## 1688 Supplier & Factory Finder Search 1688 supplier listings by product query and return supplier, factory, price and sales signals for sourcing shortlists, competitor checks and repeat-run supplier monitoring. ### Quick start Start with this working example and replace the target values with your own: ```json { "queries": [ "LED灯" ], "maxResultsPerQuery": 2, "minMonthlySales": 0, "maxPriceCny": 0, "previousSnapshot": [] } ``` The Actor writes structured results to the default Apify Dataset and can be used from the Store, API, schedules, Tasks, automations and MCP-compatible AI workflows. ### Input - `queries` — Product keywords: Wholesale product keywords. Chinese terms usually improve 1688 matching. - `maxResultsPerQuery` — Results per query: Maximum qualified offers per keyword. - `minMonthlySales` — Minimum monthly sales: Filter suppliers by observed monthly unit sales. - `maxPriceCny` — Maximum price CNY: 0 disables the price ceiling. All integration and advanced analysis fields are optional. The default example is intentionally runnable without configuring MCP or a previous-run baseline. ### Output The Dataset exposes predictable machine-readable output. Representative fields include `results`. ### Pricing This Actor uses Pay Per Event. The current factory base price is **$0.006000 per result event**. The Apify Store remains the source of truth for the price and plan/tier details shown to the buyer. ### Use cases - Run the buyer-ready workflows exposed as Apify Tasks without preparing a custom integration first. - Use the Actor from API or schedules for recurring collection, comparison or monitoring. - Feed the structured Dataset output into spreadsheets, databases, automations or AI agents. - Compare repeat runs when the product supports snapshots or previous-run inputs. ### Automation and AI Use the same Actor through Apify API, schedules, public Tasks and the Apify MCP server. Outputs are structured for downstream workflows and AI agents rather than requiring manual copy/paste. ### Limitations - Public websites and upstream APIs can change markup, access rules, rate limits or field availability without notice. - Fields that are not publicly available are returned as unavailable or omitted rather than fabricated. - Analytical outputs depend on the quality and coverage of the supplied or collected source data. - Treat marketplace, reputation, workforce, safety or commercial signals as decision support and validate material decisions against the underlying source evidence. ### Detailed documentation ### Detailed documentation ### Detailed documentation ### Detailed documentation Product query in, 1688 suppliers and sourcing data out. Supplier scoring and change intelligence are optional value layers after direct discovery. Product query in, 1688 suppliers and sourcing data out. Supplier scoring and change intelligence are optional value layers after direct discovery. Product query in, 1688 suppliers and sourcing data out. Supplier scoring and change intelligence are optional value layers after direct discovery. Product query in, 1688 suppliers and sourcing data out. Supplier scoring and change intelligence are optional value layers after direct discovery. Product query in, 1688 suppliers and sourcing data out. Supplier scoring and change intelligence are optional value layers after direct discovery. Product query in, 1688 suppliers and sourcing data out. Supplier scoring and change intelligence are optional value layers after direct discovery. Product query in, 1688 suppliers and sourcing data out. Supplier scoring and change intelligence are optional value layers after direct discovery. Product query in, 1688 suppliers and sourcing data out. Supplier scoring and change intelligence are optional value layers after direct discovery. Search 1688 by product query and return suppliers, factories, prices and sourcing fields in structured results, with optional supplier ranking and snapshot comparison. 1688 contains enormous wholesale supply, but procurement work is not finished when product rows arrive. This Actor ranks public supplier and trade signals into an explainable shortlist. ### Why use this Actor This Actor is built for users who need structured evidence and a decision layer rather than a pile of raw HTML. It extracts public-source data, normalizes the records, assigns deterministic scores that can be inspected, and emits compact actions suitable for people, APIs, MCP clients, and autonomous agents. The design favors lightweight HTTP execution where the source permits it and fails explicitly when a source blocks access instead of silently inventing rows. Snapshot input can be reused across scheduled runs to turn one-time extraction into monitoring. ### Key features - Wholesale search with structured offer and supplier fields. - Price, monthly sales, total sales, MOQ, supplier years, delivery and service tags when public. - Deterministic supplierScore and sourcingScore. - SHORTLIST\_SUPPLIER and REVIEW\_SUPPLIER actions. - Prior-snapshot price, sales, MOQ and tag deltas. - Signed 1688 H5/MTOP search transport. - Direct MTOP first, with rotating Apify proxy fallback when a cloud egress IP is challenged. ### Input Provide product keywords, result limit, optional sales/price filters and a previous snapshot. ### Output Each row is a qualified 1688 offer with supplier signals, sourcing score, change intelligence and action. ### Example ```json { "queries": [ "LED灯" ], "maxResultsPerQuery": 2, "minMonthlySales": 0, "maxPriceCny": 0, "previousSnapshot": [] } ``` The default dataset contains one billable decision-ready row per extracted entity. Aggregate summaries and reusable snapshots are stored in the default key-value store when applicable. Scores are deterministic heuristics, not claims of certainty. ### Use cases - Supplier discovery and procurement. - Dropshipping and wholesale sourcing. - Price/MOQ monitoring. - Supplier-change alerts for agents. ### Pricing Initial benchmark price: US$0.006 per qualified sourcing row before tier discounts. The Actor uses pay-per-event pricing. The primary event is one qualified row written to the default dataset. The product is designed to keep platform cost materially below the event price at normal workloads; the factory rechecks margin from live validation runs before publication. ### Limitations 1688 actively changes anti-bot behavior. Managed proxy fallback can add platform cost, and public signals do not replace supplier due diligence. Public web sources change. A successful extraction today is not a contractual guarantee that a source will preserve the same markup tomorrow. Anti-bot systems, regional network behavior, deleted content, private accounts, and login-only data can reduce coverage. This Actor does not bypass account access controls and does not claim access to private data. Use the output as operational evidence and revalidate high-stakes decisions against the original source. # Changelog This Actor's version history is a separate document: https://apify.com/quanmatrix/1688-supplier-sourcing-intelligence/changelog.md # Actor input Schema ## `queries` (type: `array`): Wholesale product keywords. Chinese terms usually improve 1688 matching. ## `maxResultsPerQuery` (type: `integer`): Maximum qualified offers per keyword. ## `minMonthlySales` (type: `integer`): Filter suppliers by observed monthly unit sales. ## `maxPriceCny` (type: `number`): 0 disables the price ceiling. ## `previousSnapshot` (type: `array`): Optional prior offers for price, sales, MOQ and tag deltas. ## `mcpConnectors` (type: `array`): Optional MCP connectors authorized in your Apify account. Use them to send or write this Actor result to tools such as Slack, Notion, GitHub, Sentry, Supabase, or another compatible MCP service. ## `mcpToolName` (type: `string`): Optional exact MCP tool name. Leave blank to let the selected MCP action preset discover a compatible tool automatically. ## `mcpToolArguments` (type: `object`): JSON object passed to the selected MCP tool. String values may use {{actor\_title}}, {{result\_summary}}, or {{result\_json}} placeholders. ## `mcpFailOnError` (type: `boolean`): When enabled, an MCP delivery error fails the Actor run. Disabled by default so data extraction and intelligence results remain available even if the external destination is unavailable. ## `mcpActionPreset` (type: `string`): Choose a safe action pattern. AUTO\_SAFE\_WRITE discovers a compatible non-destructive write tool automatically; use a specific preset for Slack, GitHub, Notion, or database delivery. ## Actor input object example ```json { "queries": [ "LED灯" ], "maxResultsPerQuery": 2, "minMonthlySales": 0, "maxPriceCny": 0, "previousSnapshot": [], "mcpToolName": "", "mcpToolArguments": {}, "mcpFailOnError": false, "mcpActionPreset": "AUTO_SAFE_WRITE" } ``` # Actor output Schema ## `results` (type: `string`): Structured rows from the default dataset. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "queries": [ "LED灯" ], "previousSnapshot": [] }; // Run the Actor and wait for it to finish const run = await client.actor("quanmatrix/1688-supplier-sourcing-intelligence").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "queries": ["LED灯"], "previousSnapshot": [], } # Run the Actor and wait for it to finish run = client.actor("quanmatrix/1688-supplier-sourcing-intelligence").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "queries": [ "LED灯" ], "previousSnapshot": [] }' | apify call quanmatrix/1688-supplier-sourcing-intelligence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,quanmatrix/1688-supplier-sourcing-intelligence" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/EXulxRbLv1ESiorLg/builds/f46s2SKRnaB7xnzn1/openapi.json