Pricing
Pay per event
Search for LinkedIn profiles with filters and extract detailed profile information, including work experience, education history, location and more. No cookies or account required.
4.6 (9)
Pricing
Pay per event
106
2.5K
700
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8.2 hours
Last modified
a day ago
You can access the LinkedIn Profile Search Scraper No Cookies ✅ Find all people 📧 programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
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The Short mode provides basic information, while the Full mode includes full detailed profile data.", "default": "Full" }, "searchQuery": { "title": "Search query (fuzzy search)", "type": "string", "description": "Query to search LinkedIn profiles. (e.g., `Founder`, `Marketing Manager`, `John Doe`). [The query supports search operators](https://www.linkedin.com/help/linkedin/answer/a524335)" }, "maxItems": { "title": "Maximum number of profiles to scrape", "maximum": 2500, "type": "integer", "description": "Maximum number of profiles to scrape. The actor will stop scraping when this limit is reached." }, "locations": { "title": "Locations Filter", "maxItems": 40, "type": "array", "description": "Filter Profiles by these LinkedIn locations. Example: `San Francisco`. LinkedIn does not always understand your text queries. For example for \"UK\" query it will apply \"Ukraine\" location, so you should use \"United Kingdom\" in this case. Try this out first in the location filter input of LinkedIn search at `https://www.linkedin.com/search/results/people/?geoUrn=%5B%22103644278%22%5D` - we will use the first suggestion from the autocomplete popup when you type your location", "items": { "type": "string" } }, "currentCompanies": { "title": "Current Company Filter", "maxItems": 40, "type": "array", "description": "Filter Profiles by these LinkedIn companies. Provide full LinkedIn URLs", "items": { "type": "string" } }, "pastCompanies": { "title": "Past Company Filter", "maxItems": 40, "type": "array", "description": "Filter Profiles by these LinkedIn past companies. Provide full LinkedIn URLs", "items": { "type": "string" } }, "schools": { "title": "School Filter", "maxItems": 40, "type": "array", "description": "Filter Profiles by these LinkedIn schools. Example: `Stanford University`.", "items": { "type": "string" } }, "currentJobTitles": { "title": "Current Job Title Filter", "maxItems": 40, "type": "array", "description": "Filter Profiles by these LinkedIn current job titles. Example: `Software Engineer`.", "items": { "type": "string" } }, "pastJobTitles": { "title": "Past Job Title Filter", "maxItems": 40, "type": "array", "description": "Filter Profiles by these LinkedIn past job titles. Example: `Software Engineer`.", "items": { "type": "string" } }, "yearsOfExperienceIds": { "title": "Years of Experience Filter", "type": "array", "description": "Filter Profiles by these LinkedIn years of experience IDs. Example: `3` for '3 to 5 years'.", "items": { "type": "string", "enum": [ "1", "2", "3", "4", "5" ], "enumTitles": [ "Less than 1 year", "1 to 2 years", "3 to 5 years", "6 to 10 years", "More than 10 years" ] } }, "yearsAtCurrentCompanyIds": { "title": "Years at Current Company Filter", "uniqueItems": true, "type": "array", "description": "Filter Profiles by these LinkedIn years at current company IDs. Example: `3` for '3 to 5 years'.", "items": { "type": "string", "enum": [ "1", "2", "3", "4", "5" ], "enumTitles": [ "Less than 1 year", "1 to 2 years", "3 to 5 years", "6 to 10 years", "More than 10 years" ] } }, "seniorityLevelIds": { "title": "Seniority Level Filter", "type": "array", "description": "Filter Profiles by these LinkedIn seniority level IDs. Example: `120` for 'Senior'.", "items": { "type": "string", "enum": [ "100", "110", "120", "130", "200", "210", "220", "300", "310", "320" ], "enumTitles": [ "In Training", "Entry Level", "Senior", "Strategic", "Entry Level Manager", "Experienced Manager", "Director", "Vice President", "CXO", "Owner / Partner" ] } }, "functionIds": { "title": "Function Filter", "type": "array", "description": "Filter Profiles by these LinkedIn function IDs. Example: `8` for 'Engineering'.", "items": { "type": "string", "enum": [ "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26" ], "enumTitles": [ "Accounting", "Administrative", "Arts and Design", "Business Development", "Community and Social Services", "Consulting", "Education", "Engineering", "Entrepreneurship", "Finance", "Healthcare Services", "Human Resources", "Information Technology", "Legal", "Marketing", "Media and Communication", "Military and Protective Services", "Operations", "Product Management", "Program and Project Management", "Purchasing", "Quality Assurance", "Real Estate", "Research", "Sales", "Customer Success and Support" ] } }, "industryIds": { "title": "Industry IDs Filter", "maxItems": 40, "type": "array", "description": "Filter Profiles by these LinkedIn industry IDs. Example: `4` for 'Software Development'. Full list: `https://github.com/HarvestAPI/linkedin-industry-codes-v2/blob/main/linkedin_industry_code_v2_all_eng_with_header.csv`", "items": { "type": "string" } }, "firstNames": { "title": "First Names Filter", "maxItems": 40, "type": "array", "description": "Filter Profiles by these LinkedIn first names. We recommend using another actor for searches by name: https://apify.com/harvestapi/linkedin-profile-search-by-name", "items": { "type": "string" } }, "lastNames": { "title": "Last Names Filter", "maxItems": 40, "type": "array", "description": "Filter Profiles by these LinkedIn last names. We recommend using another actor for searches by name: https://apify.com/harvestapi/linkedin-profile-search-by-name", "items": { "type": "string" } }, "startPage": { "title": "Start Page", "minimum": 1, "maximum": 100, "type": "integer", "description": "The page number to start scraping from. ", "default": 1 }, "takePages": { "title": "Scrape search pages", "minimum": 0, "maximum": 100, "type": "integer", "description": "The number of search pages to scrape. Each page contains 25 profiles." } } }, "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 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for LinkedIn Profile Search Scraper No Cookies ✅ Find all people 📧 from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
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