LinkedInSAFE
🔗 A Model Context Protocol (MCP) server for LinkedIn — search people, companies, and jobs, scrape profiles, and get structured data via any MCP-compatible AI client.
Overview
From the repository's own README, as read at the audited commit. Badges and raw HTML are left out.
A Model Context Protocol (MCP) server for LinkedIn. Search people, companies, and jobs, scrape profiles, and retrieve structured JSON data from any MCP-compatible AI client.
https://github.com/user-attachments/assets/50cd8629-41ee-4261-9538-40dc7d30294e
Built with FastMCP, Patchright, and a clean hexagonal architecture.
Features
Person Profile Sections
The get_person_profile tool supports granular section scraping. Request only the sections you need:
- Main profile (always included) — name, headline, location, followers, connections, about, profile image
- Experience — title, company, dates, duration, description, company logo
- Education — school, degree, dates, description, school logo
- Contact info — email, phone, websites, birthday, LinkedIn URL
- Interests — people, companies, and groups followed
- Honors and awards — title, issuer, description
- Languages — language name and proficiency level
- Posts — recent activity with reactions and timestamps
- Recommendations — received and given, with author details
Company Profile Sections
- About (always included) — overview, website, industry, size, headquarters, specialties, logo
- Posts — recent feed posts with engagement metrics
- Jobs — current open positions
Job Search Filters
The search_jobs tool supports the following filters:
95028e466d61OBSERVED · 2026-10-06Connect
Built from this server's own package name, version and transport as found in its source — not copied from anyone's documentation, so it cannot drift against a page we do not control.
claude mcp add linkedin-mcp-server -- uvx linkedin-mcp-server
{
"mcpServers": {
"linkedin-mcp-server": {
"command": "uvx",
"args": [
"linkedin-mcp-server"
]
}
}
}Exposed tools (1)
1 read · 0 write · 0 destructive.
| Tool | Risk | Description |
|---|---|---|
close_browser | read | try: |
Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | PASS |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- declared (1 observation(s))
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (1)
.pre-commit-config.yaml
Gates applied: no_behavioural_pass.
95028e466d61full audit observations/trust-audit/mcp-server/eliasbiondo__linkedin-11.json · Report an issue / request a re-scanAudit history
Every audit this server has had. A grade with a past is a grade somebody is still checking.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-06 | 95028e466d61 | SAFE | B | 89 | first audit |
Questions
What is the LinkedIn MCP server?
🔗 A Model Context Protocol (MCP) server for LinkedIn — search people, companies, and jobs, scrape profiles, and get structured data via any MCP-compatible AI client.
What tools does LinkedIn expose?
1 in total: 1 read-only, 0 that write, and 0 that can delete or overwrite. Every one is listed on this page with its risk.
Is LinkedIn safe to connect to an agent?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean server reads B.
What credentials does LinkedIn need?
No credential environment variables were found in its source, so it appears to need none.
How does LinkedIn run?
It speaks stdio and streamable-http, so it runs as a local process your client starts. It is published on PyPI as linkedin-mcp-server.
How current is this page?
The grade is for one exact copy of the source (95028e466d61), read on 2026-10-06. The repository is watched and re-audited when it changes.