# Techionik Commerce Margin MCP (`techionik9993/techionik-commerce-margin-mcp`) Actor Prompt-first MCP-ready Apify tool for AI commerce agents to check product pages, extract prices and availability, and calculate margin risk. - **URL**: https://apify.com/techionik9993/techionik-commerce-margin-mcp.md - **Developed by:** [Techionik](https://apify.com/techionik9993) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $13.00 / 1,000 product checks 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Techionik Commerce Margin MCP Techionik Commerce Margin MCP gives AI commerce agents a prompt-based way to inspect public product pages and calculate price-margin risk. It supports structured product input for batch checks and simple prompts for agent calls. ### What it does - Accepts a natural-language MCP prompt for agent-friendly use. - Also accepts structured JSON for batch/API workflows. - Returns stable dataset records with status, warnings, source URLs, and useful business fields. - Keeps the workflow lightweight by using public pages and clear failure records. ### Input Use the `prompt` field when calling this as an MCP-style tool: ```json { "prompt": "Check margin risk for SKU A100 at https://example.com/product. My cost is 22.50 and target margin is 38 percent. Return price, currency, availability, margin status, and recommended action." } ```` Structured fields remain available for API users who want explicit batch control. ### Local testing Run the unit tests and project validator from this actor folder: ```bash npm test npm run validate ``` ### Apify deployment Before deployment, confirm the active Apify account is Techionik: ```bash apify info apify push ``` Marketplace publication is intentionally skipped until final business approval. ### Output Results are written to the default Apify dataset. Each record includes a `status` field, extracted signals, warnings when something could not be fetched, and the original source input for traceability. ### Pricing Recommended pricing: USD 2.50 per 1,000 product checks. The result is valuable for sellers and agencies monitoring competitor prices, stock clues, and margin pressure. ### Limitations - Works on public pages only. - Does not bypass logins, captchas, paywalls, or site restrictions. - Some JavaScript-heavy sites may return partial data with a warning. - Final Apify Store billing still needs to be selected during marketplace publication. # Actor input Schema ## `prompt` (type: `string`): Describe the job in natural language. The actor extracts URLs, entities, and settings from this prompt, then returns structured dataset records. ## `products` (type: `array`): Optional structured fallback for API users. MCP agents should prefer prompt. ## `defaultCost` (type: `number`): Fallback unit cost used when product cost is missing. ## `defaultTargetMarginPercent` (type: `number`): Fallback target gross margin percent. ## `requestDelayMs` (type: `integer`): Polite delay in milliseconds between public page requests. ## Actor input object example ```json { "prompt": "Check margin risk for SKU A100 at https://example.com/product. My cost is 22.50 and target margin is 38 percent. Return price, currency, availability, margin status, and recommended action.", "products": [ { "sku": "SKU-1", "productUrl": "https://example.com/product", "cost": 20, "targetMarginPercent": 35, "competitorName": "Example Store" } ], "defaultTargetMarginPercent": 35, "requestDelayMs": 500 } ``` # Actor output Schema ## `results` (type: `string`): Default dataset items produced by this MCP-compatible tool. # 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 = { "prompt": "Check margin risk for SKU A100 at https://example.com/product. My cost is 22.50 and target margin is 38 percent. Return price, currency, availability, margin status, and recommended action.", "products": [ { "sku": "SKU-1", "productUrl": "https://example.com/product", "cost": 20, "targetMarginPercent": 35, "competitorName": "Example Store" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("techionik9993/techionik-commerce-margin-mcp").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 = { "prompt": "Check margin risk for SKU A100 at https://example.com/product. My cost is 22.50 and target margin is 38 percent. Return price, currency, availability, margin status, and recommended action.", "products": [{ "sku": "SKU-1", "productUrl": "https://example.com/product", "cost": 20, "targetMarginPercent": 35, "competitorName": "Example Store", }], } # Run the Actor and wait for it to finish run = client.actor("techionik9993/techionik-commerce-margin-mcp").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 '{ "prompt": "Check margin risk for SKU A100 at https://example.com/product. My cost is 22.50 and target margin is 38 percent. Return price, currency, availability, margin status, and recommended action.", "products": [ { "sku": "SKU-1", "productUrl": "https://example.com/product", "cost": 20, "targetMarginPercent": 35, "competitorName": "Example Store" } ] }' | apify call techionik9993/techionik-commerce-margin-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=techionik9993/techionik-commerce-margin-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Techionik Commerce Margin MCP", "description": "Prompt-first MCP-ready Apify tool for AI commerce agents to check product pages, extract prices and availability, and calculate margin risk.", "version": "0.1", "x-build-id": "FUiappNTj4x7JeHMD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/techionik9993~techionik-commerce-margin-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-techionik9993-techionik-commerce-margin-mcp", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/techionik9993~techionik-commerce-margin-mcp/runs": { "post": { "operationId": "runs-sync-techionik9993-techionik-commerce-margin-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/techionik9993~techionik-commerce-margin-mcp/run-sync": { "post": { "operationId": "run-sync-techionik9993-techionik-commerce-margin-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "prompt": { "title": "Prompt for this MCP tool", "type": "string", "description": "Describe the job in natural language. The actor extracts URLs, entities, and settings from this prompt, then returns structured dataset records." }, "products": { "title": "Structured products", "type": "array", "description": "Optional structured fallback for API users. MCP agents should prefer prompt." }, "defaultCost": { "title": "Default cost", "minimum": 0, "type": "number", "description": "Fallback unit cost used when product cost is missing." }, "defaultTargetMarginPercent": { "title": "Default target margin percent", "minimum": 0, "maximum": 95, "type": "number", "description": "Fallback target gross margin percent.", "default": 35 }, "requestDelayMs": { "title": "Delay between requests", "minimum": 0, "maximum": 5000, "type": "integer", "description": "Polite delay in milliseconds between public page requests.", "default": 500 } } }, "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 } } } } } } } } } } ```