Turn LinkedIn into a REST + MCP endpoint

Writ turns the LinkedIn actions you already do in a browser into a callable REST endpoint your software (and your AI agents) can call.

curl -X POST https://api.usewrit.app/v1/linkedin/run \
  -H "Authorization: Bearer wt_8f2c...a91" \
  -H "Content-Type: application/json" \
  -d '{ "input": { "query": "your search term" } }'

Record the LinkedIn task once (open a profile, then extract fields) and call it as a REST endpoint and an MCP tool. No backend project, no waiting on LinkedIn to ship an API.

1. 1
   Record the LinkedIn task once

   Open the recorder and open a profile on LinkedIn in a real browser. Writ captures each step, including login and 2FA, into a reusable workflow.

2. 2
   Publish it as an endpoint

   One click turns the workflow into a callable REST endpoint at /v1/linkedin/run and a matching MCP tool. Inputs become a typed schema.

3. 3
   Call it from anything

   Call LinkedIn from your code, a no-code tool, or an AI agent. Run it on your own machine for free, or on metered cloud.

Read the REST API docs, see what's possible on workflows, or search for another site. Free to start. See pricing.

LinkedIn has no general public API for the storefront actions most teams need. LinkedIn's API is partner-gated and does not expose the profile, search, or messaging surfaces most teams want to automate.

Writ closes that gap. Record the LinkedIn task once (or describe it to an AI session) and publish it as a REST endpoint at /v1/linkedin/run and a matching MCP tool. Writ runs on your own accounts, with your own credentials and data, on sites you are authorized to use.

Each operation below is a real LinkedIn action recorded into a workflow and exposed as a typed endpoint.

Returns structured fields such as profile fields, company page, job posting, connection: typed JSON, not raw page text.

POST your inputs, get structured output. Authenticate every call with a scoped wt_ key.

curl -X POST https://api.usewrit.app/v1/linkedin/run \
  -H "Authorization: Bearer wt_8f2c...a91" \
  -H "Content-Type: application/json" \
  -d '{ "input": { "query": "your search term" } }'

import requests

r = requests.post(
    "https://api.usewrit.app/v1/linkedin/run",
    headers={"Authorization": "Bearer wt_8f2c...a91"},
    json={"input": {"query": "your search term"}},
)
print(r.json()["output"])

{
  "run_id": "run_link_7b21",
  "status": "succeeded",
  "output": {
    "profile_fields": "...",
    "company_page": "...",
    "job_posting": "..."
  }
}

The reason LinkedIn has no usable API is the same reason it's hard to automate. Writ handles it.

Writ signs into your own LinkedIn account through a Persona with built-in 2FA (authenticator or email OTP) and operates inside that session.

Pick whichever fits the task. All three produce the same callable workflow.

Built on the same engine as the recorder and workflows.

Monitor LinkedIn for new job posting, profile change, company headcount and fire this endpoint the instant something changes.

Monitors check as fast as every 10s (10s on Enterprise). A detected change becomes an automation trigger that runs your workflow in seconds. Monitor LinkedIn ▸

Build a LinkedIn API

Record it once, then call it from your software and your AI agents. Get started free.