# MCP: Multi-Retailer MAP & Price-Violation Monitor (`seibs.co/mcp-map-price-monitor`) Actor MCP server for map-price-monitor. AI-agent tools: scan\_prices, check\_map\_violations, match\_across\_retailers, audit\_sellers across Target, Walmart, Best Buy and Newegg. x402 (USDC on Base) and Skyfire ready. For brands, MAP enforcement, repricers. - **URL**: https://apify.com/seibs.co/mcp-map-price-monitor.md - **Developed by:** [Seibs.co](https://apify.com/seibs.co) (community) - **Categories:** MCP servers, E-commerce, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% 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.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 ## MCP: Multi-Retailer MAP & Price-Violation Monitor An **MCP (Model Context Protocol) server** wrapping [`map-price-monitor`](https://apify.com/seibs.co/map-price-monitor) so AI agents (Claude, OpenAI, LangChain, LlamaIndex, Cursor, Claude Desktop) can monitor retail prices and detect MAP violations as native tool calls. > **Responsible use.** Every tool runs the upstream actor, which queries > **logged-out public product pages only** - no accounts, no login, no CAPTCHA > bypass, polite rate limits. Blocked retailers fail soft. Use within each > retailer's terms and your own legal counsel's guidance. ### Tools | Tool | What it does | |---|---| | `scan_prices` | Normalized public listings for one product across retailers (the raw price layer). | | `check_map_violations` | **MAP violations** for one product: advertised price below the threshold (supplied `map_price` or inferred advisory proxy), with graded severity, seller identity, and unauthorized-seller flags. | | `match_across_retailers` | Collapse one product into a single cross-retailer view (which retailers carry it, price spread, lowest offer). | | `audit_sellers` | Flag **unauthorized third-party resellers** of a product, with a below-MAP cross-reference. | Retailers: `target`, `bestbuy`, `newegg`, `walmart` (fully parsed) plus catalog-registered `homedepot`, `lowes`, `costco`, `bhphoto`, `wayfair`, `macys`, `microcenter`. ### Run modes - `list_tools` - emit the tool catalog (name, description, JSON schema) + the agentic-payment descriptor. **Free.** - `call_tool` - invoke one tool. Requires `tool` + `args`. - `batch` - invoke up to 10 `{tool, args}` calls in one run. ```jsonc { "mode": "call_tool", "tool": "check_map_violations", "args": { "query": "Sony WH-1000XM5", "map_price": 399.99, "retailers": ["target", "bestbuy", "newegg", "walmart"], "authorized_sellers": ["Best Buy", "Crutchfield"] } } ```` ### Pricing Flat **$0.005 per MCP tool call** (`mcp_tool_call`). The upstream actor charges its own events to the same run as pass-through (`listing_record` $0.004, `sku_match` $0.008, `map_violation_flag` $0.012). ### Agentic payments This server is **x402** (USDC on Base) and **Skyfire** ready - an AI agent can pay per tool call with no pre-provisioned API token when the operator enables MCP monetization. The payment descriptor is advertised in the `list_tools` catalog. Enable via env: `X402_ENABLED`, `X402_PAY_TO_ADDRESS`, `SKYFIRE_ENABLED`, `SKYFIRE_SELLER_ID`. # 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: scan\_prices, check\_map\_violations, match\_across\_retailers, audit\_sellers. ## `args` (type: `object`): Arguments for the selected tool. Example for check\_map\_violations: {"query": "Sony WH-1000XM5", "map\_price": 399.99, "retailers": \["target", "bestbuy", "walmart"]}. ## `calls` (type: `array`): Required when mode=batch. Each entry is an object with 'tool' and 'args'. Example: \[{"tool": "scan\_prices", "args": {"query": "Sony WH-1000XM5"}}, {"tool": "audit\_sellers", "args": {"query": "Sony WH-1000XM5", "authorized\_sellers": \["Best Buy"]}}]. Max 10 calls per run. ## Actor input object example ```json { "mode": "list_tools", "tool": "check_map_violations", "args": { "query": "Sony WH-1000XM5", "map_price": 399.99, "retailers": [ "target", "bestbuy", "newegg" ] }, "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": { "query": "Sony WH-1000XM5", "map_price": 399.99, "retailers": [ "target", "bestbuy", "newegg" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("seibs.co/mcp-map-price-monitor").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": { "query": "Sony WH-1000XM5", "map_price": 399.99, "retailers": [ "target", "bestbuy", "newegg", ], }, } # Run the Actor and wait for it to finish run = client.actor("seibs.co/mcp-map-price-monitor").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": { "query": "Sony WH-1000XM5", "map_price": 399.99, "retailers": [ "target", "bestbuy", "newegg" ] } }' | apify call seibs.co/mcp-map-price-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seibs.co/mcp-map-price-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "MCP: Multi-Retailer MAP & Price-Violation Monitor", "description": "MCP server for map-price-monitor. AI-agent tools: scan_prices, check_map_violations, match_across_retailers, audit_sellers across Target, Walmart, Best Buy and Newegg. x402 (USDC on Base) and Skyfire ready. For brands, MAP enforcement, repricers.", "version": "0.1", "x-build-id": "273teECTv9gg9Peqy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seibs.co~mcp-map-price-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seibs.co-mcp-map-price-monitor", "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-map-price-monitor/runs": { "post": { "operationId": "runs-sync-seibs.co-mcp-map-price-monitor", "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-map-price-monitor/run-sync": { "post": { "operationId": "run-sync-seibs.co-mcp-map-price-monitor", "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": [ "scan_prices", "check_map_violations", "match_across_retailers", "audit_sellers" ], "type": "string", "description": "Required when mode=call_tool. One of: scan_prices, check_map_violations, match_across_retailers, audit_sellers.", "default": "check_map_violations" }, "args": { "title": "Tool arguments (JSON object)", "type": "object", "description": "Arguments for the selected tool. Example for check_map_violations: {\"query\": \"Sony WH-1000XM5\", \"map_price\": 399.99, \"retailers\": [\"target\", \"bestbuy\", \"walmart\"]}." }, "calls": { "title": "Batch calls", "maxItems": 10, "type": "array", "description": "Required when mode=batch. Each entry is an object with 'tool' and 'args'. Example: [{\"tool\": \"scan_prices\", \"args\": {\"query\": \"Sony WH-1000XM5\"}}, {\"tool\": \"audit_sellers\", \"args\": {\"query\": \"Sony WH-1000XM5\", \"authorized_sellers\": [\"Best Buy\"]}}]. 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 } } } } } } } } } } ```