# Community Job Board Lead Scanner (`seeb/community-job-board-lead-scanner`) Actor Find service leads in community job boards by extracting company, role or project need, required skill, urgency, budget, and contact path. - **URL**: https://apify.com/seeb/community-job-board-lead-scanner.md - **Developed by:** [Techionik](https://apify.com/seeb) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 1,000 job leads 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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 ## Community Job Board Lead Scanner Find service leads in community job boards by extracting company, role or project need, required skill, urgency, budget, and contact path. Community Job Board Lead Scanner is built for one focused job: turning public source pages or pasted research snippets into usable job lead records. It does not try to be a generic webpage scraper. The parser, fields, examples, and dataset schema are shaped around this actor's specific business question. Use it when you already have public pages, listings, announcements, reviews, directories, or copied snippets and want a repeatable way to extract the information that matters without manually filling a spreadsheet. ### Who Uses It Agencies, consultants, freelancers, recruiters, outbound teams, and B2B service providers looking for companies with urgent needs. ### What It Finds The actor looks for signals connected to find service leads in community job boards by extracting company, role or project need, required skill, urgency, budget, and contact path. It keeps the output focused on fields a buyer can review, filter, enrich, or send into a CRM, spreadsheet, product backlog, procurement workflow, or research database. The extraction method is specific to this actor: Job-post parsing with role/skill detection, budget extraction, urgency scoring, contact-path recognition, and service-lead framing. ### How It Works 1. The actor accepts public URLs or pasted snippets in `jobPostSources`. 2. Public URLs are fetched when possible and converted into visible text. 3. Pasted snippets are processed directly, which is useful for pages that block automated fetching or require manual browsing. 4. Actor-specific parsing logic extracts only the fields listed below. 5. Empty or low-information inputs are skipped safely, with clean logs instead of noisy failed rows. ### Input Use `jobPostSources` for the sources you want to process. Each item can be a public URL or a focused text snippet. ```json { "jobPostSources": [ "Indie Hackers Jobs: BrightCRM is hiring a part-time HubSpot consultant next week. Apply via careers email.", "Shopify Partners Slack job: CartPilot needs a freelance Klaviyo developer ASAP for checkout retention flows. Budget $4,000.", "NoCode Founders board: DataNest seeks Bubble developer for internal dashboard redesign, remote contract." ], "maxResults": 3 } ```` ### Output Fields - `communityName` - Community, job board, Slack group, or niche source. - `companyName` - Company or organization connected to the signal. - `jobPostUrl` - Job post or hiring source URL. - `roleOrProject` - Role, project, or service need mentioned in the post. - `requiredSkill` - Skill, tool, or platform expertise requested. - `workArrangement` - Work format such as freelance, contract, part-time, or remote. - `budgetOrSalary` - Budget, salary, or project value when visible. - `urgencySignal` - Urgency based on wording such as ASAP or next week. - `contactPath` - Apply, email, DM, or contact method mentioned. - `leadAngle` - Suggested outreach angle for a service provider. ### Example Output ```json { "communityName": "Indie Hackers Jobs", "companyName": "BrightCRM", "jobPostUrl": "https://example.com/job", "roleOrProject": "a part-time HubSpot consultant", "requiredSkill": "HubSpot", "workArrangement": "part-time", "budgetOrSalary": "$4,000", "urgencySignal": "urgent", "contactPath": "apply via careers email", "leadAngle": "Offer HubSpot implementation help" } ``` ### Best Use Cases - Build a focused spreadsheet from repeated source pages. - Review public signals before sales, partnership, product, procurement, or market research work. - Monitor a category over time using the same output fields. - Turn copied notes from newsletters, communities, directories, review pages, or search results into a structured dataset. ### Tips For Better Results - Use source pages that visibly contain the signal you want this actor to extract. - For hard-to-fetch sites, paste the relevant public text snippet directly into the input. - Keep each input item focused on one page, listing, announcement, review, or profile. - Review extracted rows before making high-stakes business, legal, procurement, or security decisions. ### Limitations - The actor does not bypass logins, paywalls, private systems, CAPTCHA, or anti-bot walls. - The actor extracts from visible text and may miss information hidden behind scripts or user interactions. - Some fields may be empty when the source does not contain that information. - Output quality depends on source quality, so focused source text produces the strongest rows. # Actor input Schema ## `jobPostSources` (type: `array`): Add public URLs or paste focused text snippets. Use one source per row. The actor extracts only signals that match its specific purpose. ## `maxResults` (type: `integer`): Maximum number of useful dataset rows to save. ## Actor input object example ```json { "jobPostSources": [ "Indie Hackers Jobs: BrightCRM is hiring a part-time HubSpot consultant next week. Apply via careers email.", "Shopify Partners Slack job: CartPilot needs a freelance Klaviyo developer ASAP for checkout retention flows. Budget $4,000.", "NoCode Founders board: DataNest seeks Bubble developer for internal dashboard redesign, remote contract." ], "maxResults": 25 } ``` # Actor output Schema ## `dataset` (type: `string`): No description ## `summary` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("seeb/community-job-board-lead-scanner").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = {} # Run the Actor and wait for it to finish run = client.actor("seeb/community-job-board-lead-scanner").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 '{}' | apify call seeb/community-job-board-lead-scanner --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seeb/community-job-board-lead-scanner", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Community Job Board Lead Scanner", "description": "Find service leads in community job boards by extracting company, role or project need, required skill, urgency, budget, and contact path.", "version": "1.0", "x-build-id": "T1heuOMza8t3Wa4iR" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seeb~community-job-board-lead-scanner/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seeb-community-job-board-lead-scanner", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seeb~community-job-board-lead-scanner/runs": { "post": { "operationId": "runs-sync-seeb-community-job-board-lead-scanner", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seeb~community-job-board-lead-scanner/run-sync": { "post": { "operationId": "run-sync-seeb-community-job-board-lead-scanner", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "jobPostSources" ], "properties": { "jobPostSources": { "title": "Community job posts, niche boards, Slack job snippets, or hiring pages", "type": "array", "description": "Add public URLs or paste focused text snippets. Use one source per row. The actor extracts only signals that match its specific purpose.", "items": { "type": "string" }, "default": [ "Indie Hackers Jobs: BrightCRM is hiring a part-time HubSpot consultant next week. Apply via careers email.", "Shopify Partners Slack job: CartPilot needs a freelance Klaviyo developer ASAP for checkout retention flows. Budget $4,000.", "NoCode Founders board: DataNest seeks Bubble developer for internal dashboard redesign, remote contract." ] }, "maxResults": { "title": "Maximum results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of useful dataset rows to save.", "default": 25 } } }, "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 } } } } } } } } } } ```