# MCP: TikTok Trending Products - Product, Video & Price Feed (`seibs.co/mcp-tiktok-trending-products`) Actor MCP server for tiktok-trending-products. AI-agent tools: trending\_products, discover\_products, and trending\_in\_category - a public TikTok Shop trending feed (product + driving video + price/sales), no seller account or Shop API. x402 and Skyfire ready. For trend sites and affiliates. - **URL**: https://apify.com/seibs.co/mcp-tiktok-trending-products.md - **Developed by:** [Seibs.co](https://apify.com/seibs.co) (community) - **Categories:** MCP servers, E-commerce, AI - **Stats:** 3 total users, 1 monthly users, 70.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $5.00 / 1,000 mcp tool calls This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. Actors are written with capital "A". ## 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. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## MCP: TikTok Trending Products - Product, Video & Price Feed An **MCP server** wrapping [`seibs.co/tiktok-trending-products`](https://apify.com/seibs.co/tiktok-trending-products). It gives AI agents three tools for pulling a public trending-TikTok-Shop-products feed - the product, the **video driving it**, and its **price/sales** - with **no seller account, no TikTok Shop API, no data-security review**. x402 (USDC on Base) and Skyfire ready: an AI agent can pay per tool call with no pre-provisioned token when MCP monetization is enabled. ### Tools | Tool | What it returns | |------|-----------------| | `trending_products` | The full feed for a region + window: each product with rank, category, price + sale price, "X sold", rating, the driving video (creator + URL + embed + views), and a buy link. | | `discover_products` | Cheap reconnaissance: the trending leaderboard only (rank / product / category / trend), no price or video enrichment. | | `trending_in_category` | The feed filtered to one category (substring match, e.g. `Beauty`, `Home`, `Health`). | ### Usage This actor speaks the portfolio's MCP-over-actor protocol: a run with `mode` = `list_tools`, `call_tool`, or `batch`. **Discover the tools (free):** ```json { "mode": "list_tools" } ```` **Call one tool:** ```json { "mode": "call_tool", "tool": "trending_products", "args": { "region": "US", "period_days": 7, "max_products": 20 } } ``` **Get what's hot in a category:** ```json { "mode": "call_tool", "tool": "trending_in_category", "args": { "category": "Beauty", "region": "US" } } ``` **Batch several calls (max 10):** ```json { "mode": "batch", "calls": [ { "tool": "trending_products", "args": { "region": "US" } }, { "tool": "trending_in_category", "args": { "category": "Home" } } ] } ``` Every tool returns a uniform envelope: `{ tool, args, ok, count, items, summary, error }`. Tools never throw - an upstream failure becomes `ok: false` with an `error` string. ### Connect it to an MCP client This Actor is exposed as a remote MCP tool through Apify's hosted MCP server. Point any MCP-compatible client (Claude Desktop, Cursor, VS Code, or an OpenAI / LangChain / LlamaIndex agent) at Apify's server with this Actor enabled: ```json { "mcpServers": { "apify": { "url": "https://mcp.apify.com?tools=seibs.co/mcp-tiktok-trending-products", "headers": { "Authorization": "Bearer " } } } } ``` Get a token (free) from **Apify Console -> Settings -> API & Integrations**. The Actor then appears as a callable tool. Run `mode=list_tools` first (free) to fetch every tool's live JSON schema, then call one: ```json { "mode": "call_tool", "tool": "trending_products", "args": { } } ``` **Prefer a direct call?** Hit the Actor straight through the Apify API / SDK - no MCP client required: ```python from apify_client import ApifyClient client = ApifyClient("") run = client.actor("seibs.co/mcp-tiktok-trending-products").call(run_input={ "mode": "call_tool", "tool": "trending_products", "args": {}, }) items = client.dataset(run["defaultDatasetId"]).list_items().items ``` ### Pricing Flat **$0.005 per MCP tool call**, plus the upstream actor's pass-through PPE (`trending_product` $0.005, `enriched_product` $0.005) billed to the same run. `list_tools` is free. A tool call that returns nothing still bills the flat fee for the dispatch; upstream charges only fire on real records. ### What it's for - **Trend sites** (e.g. a daily-virals feed): let an agent refresh "today's trending products + videos" on demand. - **Affiliates / dropshippers:** ask "what's trending in Beauty this week" and get products + the videos driving them + buy links. - **AI pipelines:** a clean, typed tool surface over the public TikTok trending-commerce data - no scraping code, no seller credentials. See the upstream actor for the full feed schema, velocity/price-history (on scheduled runs), and how to power a website from the dataset. # Actor input Schema ## `mode` (type: `string`): list\_tools = emit the MCP tool catalog (free). call\_tool = invoke one tool (requires 'tool' + 'args'). batch = invoke a list of {tool, args} calls. ## `tool` (type: `string`): Required when mode=call\_tool. One of: trending\_products, discover\_products, trending\_in\_category. ## `args` (type: `object`): Arguments for the selected tool. Example for trending\_products: {"region": "US", "period\_days": 7, "max\_products": 20}. For trending\_in\_category: {"category": "Beauty", "region": "US"}. ## `calls` (type: `array`): Required when mode=batch. Each entry is an object with 'tool' and 'args'. Example: \[{"tool": "trending\_products", "args": {"region": "US"}}, {"tool": "trending\_in\_category", "args": {"category": "Home"}}]. Max 10 calls per run. ## Actor input object example ```json { "mode": "list_tools", "tool": "trending_products", "args": { "region": "US", "period_days": 7, "max_products": 20 }, "calls": [] } ``` # 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 = { "mode": "list_tools", "args": { "region": "US", "period_days": 7, "max_products": 20 } }; // Run the Actor and wait for it to finish const run = await client.actor("seibs.co/mcp-tiktok-trending-products").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 = { "mode": "list_tools", "args": { "region": "US", "period_days": 7, "max_products": 20, }, } # Run the Actor and wait for it to finish run = client.actor("seibs.co/mcp-tiktok-trending-products").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "mode": "list_tools", "args": { "region": "US", "period_days": 7, "max_products": 20 } }' | apify call seibs.co/mcp-tiktok-trending-products --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seibs.co/mcp-tiktok-trending-products", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "MCP: TikTok Trending Products - Product, Video & Price Feed", "description": "MCP server for tiktok-trending-products. AI-agent tools: trending_products, discover_products, and trending_in_category - a public TikTok Shop trending feed (product + driving video + price/sales), no seller account or Shop API. x402 and Skyfire ready. For trend sites and affiliates.", "version": "0.1", "x-build-id": "Ejz270xAxsc0jThmL" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seibs.co~mcp-tiktok-trending-products/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seibs.co-mcp-tiktok-trending-products", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seibs.co~mcp-tiktok-trending-products/runs": { "post": { "operationId": "runs-sync-seibs.co-mcp-tiktok-trending-products", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seibs.co~mcp-tiktok-trending-products/run-sync": { "post": { "operationId": "run-sync-seibs.co-mcp-tiktok-trending-products", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "list_tools", "call_tool", "batch" ], "type": "string", "description": "list_tools = emit the MCP tool catalog (free). call_tool = invoke one tool (requires 'tool' + 'args'). batch = invoke a list of {tool, args} calls.", "default": "list_tools" }, "tool": { "title": "Tool name", "enum": [ "trending_products", "discover_products", "trending_in_category" ], "type": "string", "description": "Required when mode=call_tool. One of: trending_products, discover_products, trending_in_category.", "default": "trending_products" }, "args": { "title": "Tool arguments (JSON object)", "type": "object", "description": "Arguments for the selected tool. Example for trending_products: {\"region\": \"US\", \"period_days\": 7, \"max_products\": 20}. For trending_in_category: {\"category\": \"Beauty\", \"region\": \"US\"}." }, "calls": { "title": "Batch calls", "maxItems": 10, "type": "array", "description": "Required when mode=batch. Each entry is an object with 'tool' and 'args'. Example: [{\"tool\": \"trending_products\", \"args\": {\"region\": \"US\"}}, {\"tool\": \"trending_in_category\", \"args\": {\"category\": \"Home\"}}]. Max 10 calls per run.", "default": [] } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```