Linkedin (yilin-jing) MCP Server

@yilin-jing/linkedin-mcp npm v1.2.0

Published by @yilin-jing — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.

MCP server for LinkedIn API via HarvestAPI - Returns cleaned data in TOON format for token efficiency

View on npm ↗ Repository ↗ Raw report (JSON) ↗

Trust grade

99/100

Last scanned 2026-09-07 get badge →

Trust

A · 99/100

Adoption risk for you: the threat score, then adjusted down for blast radius, publisher verification and how much the scan could see. Deterministic; every point is auditable.

Capability

Minimal

Blast radius if it went rogue — what the server’s tools could reach. Independent of trust.

Coverage

Source

How much the scan could actually inspect. Shallow coverage is stated, never hidden.

A Why this grade threat 100 − adoption risk = 99/100

The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.

1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:

The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.

2. Client adoption risk — 100 − 1 = 99. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:

Points	Adoption-risk factor
−1	publisher verification (public source) — no provenance, but the source is public and inspectable

Capability observations and info notes are shown under Findings but never scored. Open any row's finding below for the file, line and evidence behind a deduction.

Findings 0

✓ No findings. The scan raised nothing on this surface — see Coverage for how deep it could look.

Tools 17

Each tool and what it can reach — statically extracted from the published source.

get_companyno sensitive capability
get_company_postsno sensitive capability
get_groupno sensitive capability
get_jobno sensitive capability
get_postno sensitive capability
get_post_commentsno sensitive capability
get_post_reactionsno sensitive capability
get_profileno sensitive capability
get_profile_commentsno sensitive capability
get_profile_postsno sensitive capability

Show 7 more tools ↓

get_profile_reactionsno sensitive capability
search_companiesno sensitive capability
search_geo_idno sensitive capability
search_groupsno sensitive capability
search_jobsno sensitive capability
search_postsno sensitive capability
search_profilesno sensitive capability

What this scan could not see

Tools were statically extracted from the published source (17 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".

Versions 1

Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.

Version	Score	Findings	Engine	Scanned
`v1.2.0` latest	A 99/100	0	1.13.0	2026-09-07

Embed this score

Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.

Markdown (GitHub README)

[![MCP Trust Score](https://mcptrustchecker.com/registry/yilin-jing-linkedin-mcp/badge.svg)](https://mcptrustchecker.com/registry/yilin-jing-linkedin-mcp)

HTML

<a href="https://mcptrustchecker.com/registry/yilin-jing-linkedin-mcp"><img src="https://mcptrustchecker.com/registry/yilin-jing-linkedin-mcp/badge.svg" alt="MCP Trust Score" height="20"></a>

Prefer shields.io styling? Point it at https://mcptrustchecker.com/registry/yilin-jing-linkedin-mcp/badge.json via https://img.shields.io/endpoint?url=…

Verify this score yourself

The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.

npx mcptrustchecker scan @yilin-jing/linkedin-mcp --online

Use the free API → How scoring works

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