# Remote Jobs Aggregator (`agentictools/remote-jobs-aggregator`) Actor Aggregate remote jobs from multiple job boards into one clean, deduplicated feed. No API key. - **URL**: https://apify.com/agentictools/remote-jobs-aggregator.md - **Developed by:** [Ken Agland](https://apify.com/agentictools) (community) - **Categories:** Jobs, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $0.50 / 1,000 job returneds 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 ## Remote Jobs Aggregator Aggregate remote jobs from multiple free job boards into one clean, deduplicated feed. No API key. ### What it does - Pulls remote job listings from Remotive, Arbeitnow, and Jobicy. - Normalizes three different API shapes into one common schema. - Filters by keyword against title, description, and tags. - Deduplicates jobs by lowercase title plus company. - Writes a run summary with per-source counts and a company count. ### Example input ```json { "search": "python", "sources": [ "remotive", "arbeitnow", "jobicy" ], "maxPerSource": 25 } ```` ### Input | Field | Type | Description | |---|---|---| | `search` | string | Keyword matched against job title, description, and tags. Leave empty to fetch the latest jobs. | | `sources` | array | Which boards to query. Subset of `remotive`, `arbeitnow`, `jobicy`. Defaults to all three. | | `maxPerSource` | integer | Maximum jobs to keep from each source before deduplication. Default 25. | ### Output Each dataset item is one normalized job: ```json { "title": "Senior Python Engineer", "company": "Acme Inc", "url": "https://remotive.com/remote-jobs/software-dev/senior-python-engineer-123", "source": "remotive", "location": "Worldwide", "isRemote": true, "salary": "$90k - $120k", "tags": [ "python", "django", "aws" ], "category": "Software Development", "publishedAt": "2026-07-02T20:01:13.000Z", "descriptionSnippet": "We are looking for a senior Python engineer to..." } ``` #### Run summary (OUTPUT) The run's default key-value store record `OUTPUT` holds an aggregate: ```json { "query": { "search": "python", "sources": [ "remotive", "arbeitnow", "jobicy" ], "maxPerSource": 25 }, "totalJobs": 48, "perSourceCounts": { "remotive": 25, "arbeitnow": 8, "jobicy": 15 }, "companiesCount": 44, "duplicatesRemoved": 0, "generatedAt": "2026-07-04T12:00:00.000Z" } ``` ### How it works The Actor calls each selected board's public API, using each board's own keyword filter where available and filtering Arbeitnow client-side. It normalizes every result into the shared schema, strips HTML from descriptions, deduplicates across sources by title plus company, and pushes the items to the dataset. Failed sources are logged and skipped so one bad response never stops the run. It needs no API key. # Actor input Schema ## `search` (type: `string`): Keyword matched against job title, description and tags (for example "python", "react", "designer"). Leave empty to fetch the latest jobs from every source. ## `sources` (type: `array`): Which free job boards to query. Defaults to all three. ## `maxPerSource` (type: `integer`): Maximum number of jobs to keep from each source before deduplication. ## Actor input object example ```json { "search": "react", "sources": [ "remotive", "arbeitnow", "jobicy" ], "maxPerSource": 25 } ``` # 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 = { "search": "python", "sources": [ "remotive", "arbeitnow", "jobicy" ] }; // Run the Actor and wait for it to finish const run = await client.actor("agentictools/remote-jobs-aggregator").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 = { "search": "python", "sources": [ "remotive", "arbeitnow", "jobicy", ], } # Run the Actor and wait for it to finish run = client.actor("agentictools/remote-jobs-aggregator").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 '{ "search": "python", "sources": [ "remotive", "arbeitnow", "jobicy" ] }' | apify call agentictools/remote-jobs-aggregator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=agentictools/remote-jobs-aggregator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Remote Jobs Aggregator", "description": "Aggregate remote jobs from multiple job boards into one clean, deduplicated feed. No API key.", "version": "0.1", "x-build-id": "28bGzo9himZYiIIfX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/agentictools~remote-jobs-aggregator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-agentictools-remote-jobs-aggregator", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/agentictools~remote-jobs-aggregator/runs": { "post": { "operationId": "runs-sync-agentictools-remote-jobs-aggregator", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/agentictools~remote-jobs-aggregator/run-sync": { "post": { "operationId": "run-sync-agentictools-remote-jobs-aggregator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "search": { "title": "Search keyword", "type": "string", "description": "Keyword matched against job title, description and tags (for example \"python\", \"react\", \"designer\"). Leave empty to fetch the latest jobs from every source." }, "sources": { "title": "Sources", "type": "array", "description": "Which free job boards to query. Defaults to all three.", "items": { "type": "string", "enum": [ "remotive", "arbeitnow", "jobicy" ], "enumTitles": [ "Remotive", "Arbeitnow", "Jobicy" ] }, "default": [ "remotive", "arbeitnow", "jobicy" ] }, "maxPerSource": { "title": "Max jobs per source", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of jobs to keep from each source before deduplication.", "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 } } } } } } } } } } ```