# LinkedIn Pending Invitations Export (`automationagents/linkedin-pending-invitations-export`) Actor List incoming LinkedIn connection invitations waiting for approval. - **URL**: https://apify.com/automationagents/linkedin-pending-invitations-export.md - **Developed by:** [Alex Jordan](https://apify.com/automationagents) (community) - **Categories:** Automation - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.70 / 1,000 successful api calls 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 ### What does LinkedIn Pending Invitations Export do? **LinkedIn Pending Invitations Export** lists incoming LinkedIn connection invitations that are waiting for approval on the authenticated account. It is useful for queue visibility, review workflows, and downstream automation. Built on the **Apify platform**, this Actor can be scheduled, connected to webhooks, and exported through Apify dataset formats. ### Why use LinkedIn Pending Invitations Export? - **Inbox visibility** - Export pending invitations into a structured dataset - **Workflow review** - Route pending requests into approval or enrichment processes - **Reporting support** - Track incoming invitation activity outside LinkedIn UI ### How to use LinkedIn Pending Invitations Export 1. Open the Actor on Apify 2. Enter the required LinkedIn session fields 3. Start the Actor run 4. Review the output dataset for pending invitation records ### Input This Actor accepts the authenticated browser session fields required to read pending invitations from the account. #### Proxy object Use the `proxy` object to define how requests should be routed. Common fields are: - `ip` - Proxy host or endpoint URL - `port` - Proxy port - `username` - Proxy username - `password` - Proxy password **Example input:** ```json { "li_at": "AQEFAREBAAAAAXAMPLE_SESSION_TOKEN", "JSESSIONID": "ajax:1234567890123456789", "bcookie": "v=2&example-browser-cookie", "liap": "true", "li_theme_set": "app", "li_theme": "light", "timezone": "Asia/Calcutta", "bscookie": "v=1&example-secure-browser-cookie", "user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/145.0.0.0 Safari/537.36", "timezoneOffset": "5.5", "csrf-token": "ajax:1234567890123456789", "profileId": "example-self-profile-123456", "User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/145.0.0.0 Safari/537.36", "x-li-track": "{\"clientVersion\":\"1.13.455\",\"mpVersion\":\"1.13.455\",\"osName\":\"web\",\"timezoneOffset\":5.5,\"timezone\":\"Asia/Calcutta\",\"deviceFormFactor\":\"DESKTOP\",\"mpName\":\"voyager-web\",\"displayDensity\":1,\"displayWidth\":1920,\"displayHeight\":1080}", "x-li-lang": "en_US", "X-Restli-Protocol-Version": "2.0.0", "txSmSelfProfileUrl": "https://www.linkedin.com/in/example-self-profile/", "proxy": { "ip": "http://proxy.example.com", "port": "1080", "username": "user_example|session_demo|type_mobile|lon_73.8502|lat_18.5211", "password": "example_proxy_password" } } ```` ### Output The Actor writes the extracted invitation records to the default dataset. **Example output:** ```json { "success": true, "response": [ { "firstName": "Avery", "lastName": "Stone", "headline": "Revenue Operations Manager", "liProfilePublicUrl": "https://www.linkedin.com/in/avery-stone-demo", "liProfileId": "ACoAAC8EXAMPLEPROFILEID", "invitationType": "RECEIVED", "sentAt": "2026-06-15T12:00:00.000Z", "timestamp": "2026-06-17T08:10:00.000Z" } ] } ``` ### Pricing / Cost estimation **$0.0017 per successful API call** on Apify. ### Support If you need adjustments for your workflow, use the Actor Issues tab or your internal support channel. # Actor input Schema ## `li_at` (type: `string`): LinkedIn session cookie used for authenticated requests. ## `JSESSIONID` (type: `string`): LinkedIn JSESSIONID cookie value from your authenticated browser session. ## `bcookie` (type: `string`): LinkedIn browser identification cookie. ## `liap` (type: `string`): LinkedIn account cookie used by the authenticated session. ## `li_theme_set` (type: `string`): Theme preference cookie captured from the same browser session. ## `li_theme` (type: `string`): LinkedIn theme cookie from the authenticated browser session. ## `timezone` (type: `string`): Browser timezone string, for example Asia/Kolkata or America/New\_York. ## `bscookie` (type: `string`): LinkedIn secure browser cookie used together with other session cookies. ## `user-agent` (type: `string`): Lowercase user-agent header value from the browser session. ## `timezoneOffset` (type: `string`): Browser timezone offset value captured from the logged-in session, such as 5.5 or -4. ## `csrf-token` (type: `string`): CSRF token used for authenticated LinkedIn requests. ## `profileId` (type: `string`): LinkedIn profile identifier for the authenticated account used to fetch pending invitations. ## `User-Agent` (type: `string`): Standard User-Agent header value from the same authenticated browser session. ## `x-li-track` (type: `string`): LinkedIn tracking header value captured from browser network requests. ## `x-li-lang` (type: `string`): LinkedIn language header, usually a locale such as en\_US. ## `X-Restli-Protocol-Version` (type: `string`): LinkedIn Rest.li protocol version header, usually 2.0.0. ## `txSmSelfProfileUrl` (type: `string`): Your own LinkedIn profile URL from the same logged-in session. ## `proxy` (type: `object`): Proxy configuration object passed to the backend. Common fields are ip, port, username, and password. ## Actor input object example ```json {} ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("automationagents/linkedin-pending-invitations-export").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("automationagents/linkedin-pending-invitations-export").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 automationagents/linkedin-pending-invitations-export --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automationagents/linkedin-pending-invitations-export", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Pending Invitations Export", "description": "List incoming LinkedIn connection invitations waiting for approval.", "version": "0.1", "x-build-id": "Ix0zKz8byaBv84aZC" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automationagents~linkedin-pending-invitations-export/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automationagents-linkedin-pending-invitations-export", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automationagents~linkedin-pending-invitations-export/runs": { "post": { "operationId": "runs-sync-automationagents-linkedin-pending-invitations-export", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automationagents~linkedin-pending-invitations-export/run-sync": { "post": { "operationId": "run-sync-automationagents-linkedin-pending-invitations-export", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "JSESSIONID", "User-Agent", "X-Restli-Protocol-Version", "bcookie", "bscookie", "csrf-token", "li_at", "li_theme", "li_theme_set", "liap", "profileId", "proxy", "timezone", "timezoneOffset", "txSmSelfProfileUrl", "user-agent", "x-li-lang", "x-li-track" ], "properties": { "li_at": { "title": "li_at", "type": "string", "description": "LinkedIn session cookie used for authenticated requests." }, "JSESSIONID": { "title": "JSESSIONID", "type": "string", "description": "LinkedIn JSESSIONID cookie value from your authenticated browser session." }, "bcookie": { "title": "bcookie", "type": "string", "description": "LinkedIn browser identification cookie." }, "liap": { "title": "liap", "type": "string", "description": "LinkedIn account cookie used by the authenticated session." }, "li_theme_set": { "title": "li_theme_set", "type": "string", "description": "Theme preference cookie captured from the same browser session." }, "li_theme": { "title": "li_theme", "type": "string", "description": "LinkedIn theme cookie from the authenticated browser session." }, "timezone": { "title": "timezone", "type": "string", "description": "Browser timezone string, for example Asia/Kolkata or America/New_York." }, "bscookie": { "title": "bscookie", "type": "string", "description": "LinkedIn secure browser cookie used together with other session cookies." }, "user-agent": { "title": "user-agent", "type": "string", "description": "Lowercase user-agent header value from the browser session." }, "timezoneOffset": { "title": "timezoneOffset", "type": "string", "description": "Browser timezone offset value captured from the logged-in session, such as 5.5 or -4." }, "csrf-token": { "title": "csrf-token", "type": "string", "description": "CSRF token used for authenticated LinkedIn requests." }, "profileId": { "title": "profileId", "type": "string", "description": "LinkedIn profile identifier for the authenticated account used to fetch pending invitations." }, "User-Agent": { "title": "User-Agent", "type": "string", "description": "Standard User-Agent header value from the same authenticated browser session." }, "x-li-track": { "title": "x-li-track", "type": "string", "description": "LinkedIn tracking header value captured from browser network requests." }, "x-li-lang": { "title": "x-li-lang", "type": "string", "description": "LinkedIn language header, usually a locale such as en_US." }, "X-Restli-Protocol-Version": { "title": "X-Restli-Protocol-Version", "type": "string", "description": "LinkedIn Rest.li protocol version header, usually 2.0.0." }, "txSmSelfProfileUrl": { "title": "txSmSelfProfileUrl", "type": "string", "description": "Your own LinkedIn profile URL from the same logged-in session." }, "proxy": { "title": "proxy", "type": "object", "description": "Proxy configuration object passed to the backend. Common fields are ip, port, username, and password." } } }, "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 } } } } } } } } } } ```