Mark Message As Read

Mark a LinkedIn conversation as read so unread counts and notification state stay accurate.

Edges is not related to LinkedIn and is not an official LinkedIn product.

API Endpoint

POST/v1/actions/linkedin-mark-message-as-read/run/live

Parameters

Input Parameters

Integration Parameters

Guide

What Mark Message As Read does

Mark Message As Read flips a LinkedIn conversation's unread state to read, so your inbox counter and notification badges reflect what your automation has actually processed. You get a single-record primitive that keeps your inbox honest when messages are handled outside the LinkedIn UI.

It runs on the LinkedIn level and uses your connected LinkedIn session, so every state change is attributable to your account.

How it works

You pass the conversation ID or thread URN. Edges signs the request with your authenticated LinkedIn session, sends the read receipt, and returns a typed result confirming the new state. The action runs on Edges infrastructure with safe pacing, so you do not manage cookies or retries yourself.

The operation is synchronous. By the time the run completes, the conversation no longer appears in your unread count, the notification badge updates, and the read receipt is visible to the other participant if their settings allow it.

When to use Mark Message As Read

Use Mark Message As Read when your outside-LinkedIn workflow has already processed a conversation — a CRM sync, a Slack notification, a ticket routing — and you want the LinkedIn UI to match reality. It is a small primitive, but it keeps inbox state and notification hygiene aligned with the LinkedIn messaging & outreach API workflow.

It is also useful for teams running shared-inbox plays, where one teammate triages while another replies, and neither wants stale unread counts clouding triage.

Use cases

  • CRM handoff. When a conversation is logged into your CRM, mark it read on LinkedIn so triagers do not re-process it.
  • Shared inbox triage. Team members mark handled conversations read from the tool they work in, not by re-opening LinkedIn.
  • Automated acknowledgements. After an auto-reply fires, mark the incoming message read so the conversation clears.
  • Notification budget. Keep unread counts accurate for accounts where high volume would otherwise drown real signals.
  • Reporting accuracy. Ensure inbox analytics reflect actual team behavior, not LinkedIn's passive counter.

Best practices

  • Chain after processing. Only mark read once the downstream step (CRM write, Slack alert, sequencer enroll) has confirmed success — otherwise you lose the retry signal.
  • Respect sender expectations. Read receipts are visible to the sender in some configurations. Treat this as a committed acknowledgement.
  • Keep per-account volume reasonable. Edges paces automatically; avoid spamming the endpoint as a sweep from other automations.
  • Log before mutating. Write the conversation state into your own system before the Mark Message As Read call, so you can audit divergence later.

Common questions

How many conversations can I mark read per run?

One per run. Mark Message As Read is a per-record primitive — for a sweep, loop it over an input list from Extract LinkedIn Conversations.

Does this use my LinkedIn account or a shared pool?

Your LinkedIn account. You connect LinkedIn to Edges once, and every state update runs through that authenticated session.

Can I chain Mark Message As Read with other Edges actions?

Yes. Typical patterns chain Extract LinkedIn Conversations upstream, process each thread with Extract LinkedIn Messages, then finish with Mark Message As Read so the inbox reflects processing.

Get started

Add Mark Message As Read to any inbox-handling flow on Edges, or call it directly from the Edges API as the cleanup step after a CRM or Slack write. Browse the full Actions library for the rest of the inbox automation primitives.

Code Examples

bash
curl -X POST "https://api.edges.run/v1/actions/linkedin-mark-message-as-read/run/live" \
  -H "X-API-KEY: <YOUR_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{
  "identity_ids": [
    "your-identity-uuid"
  ],
  "identity_mode": "direct",
  "input": {
    "linkedin_thread_id": "example_value",
    "custom_data": "example_value"
  }
}'

Output Example

{
  "linkedin_thread_id": "example-123"
}

Explore More Actions

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