# Linkedin Company Decision Makers - MCP connector (`techforce.global/linkedin-company-decision-makers`) Actor Enter a company name, get its decision makers — founders, C-suite, VPs & directors with LinkedIn profiles, & roles. Deliver to Notion, Slack, Jira & more via MCP. - **URL**: https://apify.com/techforce.global/linkedin-company-decision-makers.md - **Developed by:** [Techforce Global](https://apify.com/techforce.global) (community) - **Categories:** MCP servers, Social media, Automation - **Stats:** 2 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ### LinkedIn Decision Maker Finder & MCP Connector Find the **decision makers at any company** — founders, C-suite, VPs, directors, and heads of department — with their LinkedIn profiles, roles, and locations. **No manual LinkedIn searching, no guessing who to contact, no scraping dead ends.** Built for B2B sales teams, recruiters, and founders who need an accurate contact shortlist for a target account in seconds — not an afternoon of digging through LinkedIn. > **Type a company name → get its decision makers → deliver them straight into your CRM, Notion, Slack, or Jira.** --- ### ⭐ Why This Actor? - ✅ **Just enter a company name** — no LinkedIn login, cookies, or session tokens required - ✅ **Decision makers only** — smart role classification keeps founders, C-suite, VPs, directors & heads; filters out junior noise - ✅ **Role & seniority detection** — every profile is matched against 40+ leadership titles and ranked by seniority - ✅ **Verified against the target company** — results are gated so you get people _at that company_, not lookalikes - ✅ **Deliver anywhere via MCP connectors** — push results straight into Notion, Slack, Jira, GitHub, Linear, Airtable, and more - ✅ **Export-ready** — JSON, CSV, Excel, or direct API integration for your CRM or outreach tool --- ### 📝 Use Cases & ROI | Use Case | Time Saved | What You Get | | ---------------------------- | ------------------ | ------------------------------------------------------------------ | | **B2B Sales Prospecting** | 3–6 hrs/account | The right decision makers to contact at each target company | | **Account-Based Marketing** | 2–5 hrs/campaign | Org-level contact maps for your named accounts | | **Recruiting & Headhunting** | 2–4 hrs/search | Leadership contacts at competitor or client companies | | **Partnership Sourcing** | 1–3 hrs/initiative | Founders and executives to pitch directly | | **CRM Enrichment** | Ongoing | Fresh decision-maker records piped into your CRM via API/connector | --- ### 🚀 How to Use 1. Open the Actor on Apify 2. Enter the **Company Name** you want to map (e.g. `"Techforce Global"`) 3. Set **Max Profiles** — how many decision makers to collect (default: 20) 4. _(Optional)_ Pick an **MCP connector** to deliver results into Notion, Slack, Jira, etc. 5. Click **Run** — results are ready in minutes 6. Download as CSV, Excel, or JSON — or let the connector push them into your tools automatically > 💡 First time with a connector? Run once with a connector selected — the run log prints the connector's available tool names, so you know what to put in **Connector tool name**. --- ### 🧩 Input Configuration | Field | Type | Required | Description | | -------------------- | --------- | -------- | ------------------------------------------------------------------------------------------------------------ | | `company_name` | String | ✔️ Yes | Exact company name to find decision makers for. | | `max_profiles` | Integer | Optional | Maximum number of unique decision-maker profiles to collect (1–200). Default: `20`. | | `mcpConnector` | Connector | Optional | Deliver results into a connector you've authorized (Notion, Slack, Jira, GitHub, Linear, Airtable, …). | | `deliveryMode` | Enum | Optional | `perProfile` (one call per decision maker), `summary` (one combined call), or `none`. Default: `perProfile`. | | `mcpTool` | String | Optional | Tool to call on the connector (e.g. `create_page`, `send_message`, `create_issue`). | | `mcpArguments` | Object | Optional | Arguments for the tool; string values support `{placeholders}`. | | `mcpMessageTemplate` | String | Optional | Markdown template rendered per profile, exposed as the `{message}` placeholder. | #### Example — Just find decision makers ```json { "company_name": "Techforce Global", "max_profiles": 20 } ```` #### Example — Find and deliver to Slack ```json { "company_name": "Prismetric", "max_profiles": 15, "mcpConnector": "", "deliveryMode": "perProfile", "mcpTool": "send_message", "mcpArguments": { "channel": "#target-accounts", "text": "{message}" }, "mcpMessageTemplate": "*{name}* — {title}\n{location}\n{linkedin_url}" } ``` #### Example — Find and create Notion pages ```json { "company_name": "Hyperlink Infosystem", "max_profiles": 25, "mcpConnector": "", "deliveryMode": "perProfile", "mcpTool": "create_page", "mcpArguments": { "parent": "", "title": "{name} — {title}", "url": "{linkedin_url}" } } ``` #### Placeholders available in arguments / template `{name}` · `{linkedin_url}` · `{location}` · `{title}` · `{headline}` · `{message}` *** ### 📦 Output Fields Each record includes: | Field | Description | | -------------- | ----------------------------------------------------------------- | | `name` | Decision maker's full name | | `linkedin_url` | Normalized link to their LinkedIn profile | | `location` | Location as shown alongside the profile (city / region / country) | | `title` | Best-detected role/title (e.g. `"VP and Co-Founder"`, `"CTO"`) | | `headline` | Short professional headline / profile summary snippet | #### Example Output ```json [ { "name": "Urvi Shah", "linkedin_url": "https://www.linkedin.com/in/urvi-shah", "location": "Ahmedabad, India", "title": "VP and Co-Founder", "headline": "VP and Co-Founder of Techforce Global — building high-performance web scrapers & AI automation." } ] ``` > You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. *** ### 🔌 Integrations & Delivery Deliver decision makers into any MCP connector you've authorized in Apify — no glue code, no webhooks: - **Notion** — create a page/row per decision maker - **Slack / Discord** — post contacts to a channel - **Jira / GitHub / Linear** — open issues or tasks for outreach - **Airtable / Google Sheets** — append structured rows - …or any other MCP-compatible connector Credentials stay private — delivery runs through the **Apify MCP Proxy**, so the Actor never sees your connector tokens. You can also consume the dataset directly via the **Apify API**, or wire it into **n8n, Zapier, and Make**. *** ### ⚡ Real-time API (Standby mode) Beyond one-off runs, this Actor can run in **Standby mode** — a warm HTTP endpoint that returns decision makers **instantly**, no run to start and wait for. Perfect for enriching a CRM record on demand or powering a "find decision makers" button in your app. **Endpoint:** `GET /` | Query param | Required | Description | | -------------- | -------- | -------------------------------------------------------- | | `company_name` | ✔️ Yes | Company to find decision makers for. | | `max_profiles` | Optional | How many profiles to return (1–20, default 5). | ```bash curl "https:///?company_name=Techforce%20Global&max_profiles=10" \ -H "Authorization: Bearer " ``` **Response:** ```json { "company": "Techforce Global", "count": 2, "decision_makers": [ { "name": "Urvi Shah", "linkedin_url": "https://www.linkedin.com/in/urvi-shah", "location": "Ahmedabad, India", "title": "VP and Co-Founder", "headline": "VP and Co-Founder of Techforce Global — high-performance web scrapers & AI automation." } ] } ``` > Standby returns results directly in the HTTP response. For dataset storage and MCP-connector delivery (Notion, Slack, Jira, …), use a normal run with the inputs above. *** ### 🆘 Support For issues, custom sourcing requests, or feature suggestions: **Email**: bhavin.shah@techforceglobal.com *** #### Need a Custom Pipeline? Want multi-company batch runs, deeper enrichment (emails, phone numbers), or a full CRM integration? #### [📅 Book a Free 15-min Consultation](https://calendly.com/techforce-infotech-pvt-ltd/intro-meeting?month=2026-01) *** Made with ❤️ by **[Techforce](https://www.techforceglobal.com)** Specialists in High-Performance Web Scrapers and AI Automation. *** ### Disclaimer This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by LinkedIn or Google. LinkedIn® is a registered trademark of Microsoft Corporation; all trademarks are property of their respective owners. The Actor collects only publicly available information surfaced through public search-engine results and does not log into, or scrape behind the authentication of, any platform. Use the data responsibly and in compliance with applicable laws (including GDPR/CCPA) and the terms of the platforms you operate on. # Actor input Schema ## `company_name` (type: `string`): Exact company name to search for. ## `max_profiles` (type: `integer`): Maximum number of unique decision-maker profiles to collect and save to dataset. ## `mcpConnector` (type: `string`): Optionally deliver the found decision makers into a connector you have authorized — Notion, Slack, Linear, Airtable, Jira, GitHub, or any MCP-compatible connector. Leave empty to only save results to the dataset. ## `deliveryMode` (type: `string`): How to deliver to the connector: 'perProfile' (one call per decision maker), 'summary' (one call with all profiles combined), or 'none' (save to dataset only). ## `mcpTool` (type: `string`): Name of the tool to call on the connector (e.g. 'create\_page' for Notion, 'send\_message' for Slack, 'create\_issue' for Jira/GitHub). If unsure, run once with a connector selected — the log lists the connector's available tools. ## `mcpArguments` (type: `object`): Arguments passed to the connector tool. String values support {placeholders} from each profile: {name}, {linkedin\_url}, {location}, {title}, {headline}, and {message} (the rendered template below). Example for Slack: {"channel": "#leads", "text": "{message}"}. ## `mcpMessageTemplate` (type: `string`): Optional Markdown template rendered per profile and exposed as the {message} placeholder in the tool arguments. Example: '*{name}* — {title}\n{location}\n{linkedin\_url}'. ## Actor input object example ```json { "company_name": "Techforce Global", "max_profiles": 5, "deliveryMode": "perProfile", "mcpTool": "", "mcpArguments": {}, "mcpMessageTemplate": "" } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "company_name": "Techforce Global" }; // Run the Actor and wait for it to finish const run = await client.actor("techforce.global/linkedin-company-decision-makers").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 = { "company_name": "Techforce Global" } # Run the Actor and wait for it to finish run = client.actor("techforce.global/linkedin-company-decision-makers").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 '{ "company_name": "Techforce Global" }' | apify call techforce.global/linkedin-company-decision-makers --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=techforce.global/linkedin-company-decision-makers", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Company Decision Makers - MCP connector", "description": "Enter a company name, get its decision makers — founders, C-suite, VPs & directors with LinkedIn profiles, & roles. Deliver to Notion, Slack, Jira & more via MCP.", "version": "0.0", "x-build-id": "IXdGW8a8ImhRVel0Y" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/techforce.global~linkedin-company-decision-makers/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-techforce.global-linkedin-company-decision-makers", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/techforce.global~linkedin-company-decision-makers/runs": { "post": { "operationId": "runs-sync-techforce.global-linkedin-company-decision-makers", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/techforce.global~linkedin-company-decision-makers/run-sync": { "post": { "operationId": "run-sync-techforce.global-linkedin-company-decision-makers", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "company_name" ], "properties": { "company_name": { "title": "Company Name", "type": "string", "description": "Exact company name to search for." }, "max_profiles": { "title": "Max Profiles", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum number of unique decision-maker profiles to collect and save to dataset.", "default": 5 }, "mcpConnector": { "title": "Deliver to (MCP connector)", "type": "string", "description": "Optionally deliver the found decision makers into a connector you have authorized — Notion, Slack, Linear, Airtable, Jira, GitHub, or any MCP-compatible connector. Leave empty to only save results to the dataset." }, "deliveryMode": { "title": "Delivery mode", "enum": [ "perProfile", "summary", "none" ], "type": "string", "description": "How to deliver to the connector: 'perProfile' (one call per decision maker), 'summary' (one call with all profiles combined), or 'none' (save to dataset only).", "default": "perProfile" }, "mcpTool": { "title": "Connector tool name", "type": "string", "description": "Name of the tool to call on the connector (e.g. 'create_page' for Notion, 'send_message' for Slack, 'create_issue' for Jira/GitHub). If unsure, run once with a connector selected — the log lists the connector's available tools.", "default": "" }, "mcpArguments": { "title": "Connector tool arguments", "type": "object", "description": "Arguments passed to the connector tool. String values support {placeholders} from each profile: {name}, {linkedin_url}, {location}, {title}, {headline}, and {message} (the rendered template below). Example for Slack: {\"channel\": \"#leads\", \"text\": \"{message}\"}.", "default": {} }, "mcpMessageTemplate": { "title": "Message template", "type": "string", "description": "Optional Markdown template rendered per profile and exposed as the {message} placeholder in the tool arguments. Example: '*{name}* — {title}\\n{location}\\n{linkedin_url}'.", "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 } } } } } } } } } } ```