# MCP Buyer Signal Monitor Tool (`glowing_glove/mcp-buyer-signal-monitor-tool`) Actor MCP-ready buyer-signal monitor for AI sales agents using a prompt-first interface. Analyze public company pages for hiring, growth, automation, AI, and buying signals. - **URL**: https://apify.com/glowing\_glove/mcp-buyer-signal-monitor-tool.md - **Developed by:** [Ushba Khan](https://apify.com/glowing_glove) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $6.00 / 1,000 company monitoreds 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 Buyer Signal Monitor Tool ### What it does MCP-ready tool for AI sales agents to analyze public company pages for hiring, growth, automation, AI, and buyer-intent signals. This is packaged for Apify deployment and exposed to AI clients through the Apify MCP server as a callable MCP tool. The public-facing name, schema, output, pricing, and listing copy are MCP-first. ### Buyer AI sales agents, B2B SaaS teams, outbound agencies ### Input See input_schema.json and .actor/input_schema.json for the exact MCP-compatible input schema. ### Output See output_schema.json for the structured result contract. Outputs include status/warnings fields so AI agents can reason about partial or failed records. ### Pricing Recommended pricing: **USD 6.00 per 1,000 companies monitored**. ### Categories Lead generation, Business ### Local testing `ash npm install npm test npm run validate apify validate-schema npm start ` ### Apify MCP usage After deployment, connect an MCP client to https://mcp.apify.com and include this tool by selecting it in the Apify MCP configurator or by adding it to the MCP ools parameter. ### Marketplace note This is MCP-ready display copy. Marketplace publication still requires Ushba's business approval. ### Apify deployment This MCP tool is deployed to Apify so it can be exposed through `https://mcp.apify.com` to MCP clients. Deployment checks: ```bash npm test npm run validate apify validate-schema apify info apify push ```` Marketplace publication is separate and requires Ushba's business approval. # Actor input Schema ## `prompt` (type: `string`): Natural-language instruction from an MCP client or AI agent. The tool extracts URLs/entities/settings from this prompt and runs the requested workflow. ## `companies` (type: `array`): Optional structured fallback for API users. MCP agents should prefer prompt. ## `signalKeywords` (type: `array`): Custom buying-signal keywords to search for in public pages. ## `maxUrlsPerCompany` (type: `integer`): Maximum public URLs to fetch and analyze for each company. ## `requestDelayMs` (type: `integer`): Polite delay in milliseconds between public page requests. ## Actor input object example ```json { "prompt": "Monitor buyer intent for Example SaaS at https://example.com/careers for the Head of Sales persona. Look for hiring, RevOps, CRM, automation, growth, and AI signals.", "companies": [ { "companyName": "Example SaaS", "urls": [ "https://example.com/careers" ], "targetPersona": "Head of Sales" } ], "signalKeywords": [ "hiring", "sales operations", "revops", "crm", "automation" ], "maxUrlsPerCompany": 5, "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": "Monitor buyer intent for Example SaaS at https://example.com/careers for the Head of Sales persona. Look for hiring, RevOps, CRM, automation, growth, and AI signals.", "companies": [ { "companyName": "Example SaaS", "urls": [ "https://example.com/careers" ], "targetPersona": "Head of Sales" } ], "signalKeywords": [ "hiring", "sales operations", "revops", "crm", "automation" ] }; // Run the Actor and wait for it to finish const run = await client.actor("glowing_glove/mcp-buyer-signal-monitor-tool").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": "Monitor buyer intent for Example SaaS at https://example.com/careers for the Head of Sales persona. Look for hiring, RevOps, CRM, automation, growth, and AI signals.", "companies": [{ "companyName": "Example SaaS", "urls": ["https://example.com/careers"], "targetPersona": "Head of Sales", }], "signalKeywords": [ "hiring", "sales operations", "revops", "crm", "automation", ], } # Run the Actor and wait for it to finish run = client.actor("glowing_glove/mcp-buyer-signal-monitor-tool").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": "Monitor buyer intent for Example SaaS at https://example.com/careers for the Head of Sales persona. Look for hiring, RevOps, CRM, automation, growth, and AI signals.", "companies": [ { "companyName": "Example SaaS", "urls": [ "https://example.com/careers" ], "targetPersona": "Head of Sales" } ], "signalKeywords": [ "hiring", "sales operations", "revops", "crm", "automation" ] }' | apify call glowing_glove/mcp-buyer-signal-monitor-tool --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=glowing_glove/mcp-buyer-signal-monitor-tool", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "MCP Buyer Signal Monitor Tool", "description": "MCP-ready buyer-signal monitor for AI sales agents using a prompt-first interface. Analyze public company pages for hiring, growth, automation, AI, and buying signals.", "version": "1.0", "x-build-id": "pmqqaUErFInjvAwE7" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/glowing_glove~mcp-buyer-signal-monitor-tool/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-glowing_glove-mcp-buyer-signal-monitor-tool", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/glowing_glove~mcp-buyer-signal-monitor-tool/runs": { "post": { "operationId": "runs-sync-glowing_glove-mcp-buyer-signal-monitor-tool", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/glowing_glove~mcp-buyer-signal-monitor-tool/run-sync": { "post": { "operationId": "run-sync-glowing_glove-mcp-buyer-signal-monitor-tool", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "MCP agent prompt", "type": "string", "description": "Natural-language instruction from an MCP client or AI agent. The tool extracts URLs/entities/settings from this prompt and runs the requested workflow." }, "companies": { "title": "Structured companies", "type": "array", "description": "Optional structured fallback for API users. MCP agents should prefer prompt." }, "signalKeywords": { "title": "Signal keywords", "type": "array", "description": "Custom buying-signal keywords to search for in public pages.", "items": { "type": "string" } }, "maxUrlsPerCompany": { "title": "Max URLs per company", "minimum": 1, "maximum": 10, "type": "integer", "description": "Maximum public URLs to fetch and analyze for each company.", "default": 5 }, "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 } } } } } } } } } } ```