LinkedIn Profile Enrich
Give it a LinkedIn profile URL, get back the full profile — work experience, education and skills.
- Tool
linkedin_profile_enrich- Cost
- 1 credit
- Category
- LinkedIn Profile
- Required input
profile_url- Returns
- Work experience, education, skills
What it does
- Enriches a LinkedIn profile from its URL. A bare username works too — you do not need the full
https://linkedin.com/in/...form. - Returns the depth of the profile: work experience, education and skills.
- One profile per call, flat cost.
Use it when you need the person’s history. If you only need a contact record — title, company, contact details — enrich_person is the right tool and it accepts more identifier types (name, email, organization) rather than requiring a URL.
It does not return an email address. Chain find_work_email for that.
Parameters
| Parameter | Type | Required | Notes |
|---|---|---|---|
profile_url | string | Yes | Full profile URL or username |
How to use it
Connect the MCP server
Follow the setup guide for your client. Browser sign-in, no API key.
Enrich one profile
Pull the full LinkedIn profile for linkedin.com/in/janedoeAsk for the part you care about
Enrich linkedin.com/in/janedoe and summarise her last three roles,
with company and tenure for each.Enrich a list
Enrich these 25 LinkedIn URLs. For each, return name, current title,
current company, years at current company, and top skills.
Report how many credits you used.Example prompts
| Ask your client | What you get back |
|---|---|
| ”Enrich linkedin.com/in/janedoe” | Full profile — experience, education, skills |
| ”What companies has this person worked at before?” | Work history from the profile |
| ”Enrich these 25 URLs and give me a table of title, company and tenure” | One row per profile |
| ”Get me Jane Doe’s email” | Better served by find_work_email — this tool returns no email |
Best prompting practices
- Say “full profile” or “work history”. That routes your client here rather than to
enrich_person, which returns a shallower contact record. - Ask for the fields you want in the output. The full profile is large. Naming the fields keeps the answer readable and the table consistent across rows.
- Deduplicate the list first. Two identical URLs cost 2 credits for the same profile.
- Cap the batch. “Stop after 50 and report credits used” keeps a long list predictable.
- Enrich after you filter. Search first with
find_people, then enrich only the profiles that survived the filter.
Output
{
"name": "Jane Doe",
"profile_url": "https://linkedin.com/in/janedoe",
"experience": [
{ "title": "VP Sales", "company": "Stripe" }
],
"education": [
{ "school": "MIT", "degree": "BSc" }
],
"skills": ["Enterprise Sales", "SaaS"]
}Credits and limits
1 credit per profile, flat. Run check_credits (free) before a large batch.
Private or restricted profiles return thin results. A sparse response is a coverage limit, not an error — do not re-run the same URL expecting a different answer, because the second call costs another credit.
Related tools
| Tool | Use it instead when |
|---|---|
enrich_person | You want a contact record, or you only have a name, email or company — 1 credit |
find_work_email | You need the email address, not the history |
linkedin_profile_posts | You want what they publish, not who they are |
check_job_change | You only need to know whether they moved recently |
Next steps
- All MCP tools — the full catalogue with credit costs
- MCP use cases — profile research workflows
- AI for Sales Reps — workflows that chain this tool into a list build
Keep learning
Two courses take these tools past the reference page — clustered by GTM job, then chained into workflows.