Linkedin (ldraney) MCP Server
@ldraney/mcp-linkedin
npm
v0.3.1
Published by @ldraney — no publish provenance and no public repository, so the publisher could not be verified and the source cannot be independently located.
MCP server for managing LinkedIn posts
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 − 2 = 98. 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 |
|---|---|
| −2 | publisher verification (unlinked) — no provenance/repo link, but the shipped source was fully read |
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
Tools 21
Each tool and what it can reach — statically extracted from the published source.
linkedin_add_commentno sensitive capabilitylinkedin_add_reactionno sensitive capabilitylinkedin_cancel_scheduled_postno sensitive capabilitylinkedin_create_pollno sensitive capabilitylinkedin_create_postno sensitive capabilitylinkedin_create_post_with_documentno sensitive capabilitylinkedin_create_post_with_imageno sensitive capabilitylinkedin_create_post_with_linkno sensitive capabilitylinkedin_create_post_with_multi_imagesno sensitive capabilitylinkedin_create_post_with_videono sensitive capability
Show 11 more tools ↓
linkedin_delete_postno sensitive capabilitylinkedin_exchange_codeno sensitive capabilitylinkedin_get_auth_urlno sensitive capabilitylinkedin_get_my_postsno sensitive capabilitylinkedin_get_scheduled_postno sensitive capabilitylinkedin_get_user_infono sensitive capabilitylinkedin_list_scheduled_postsno sensitive capabilitylinkedin_refresh_tokenno sensitive capabilitylinkedin_save_credentialsno sensitive capabilitylinkedin_schedule_postno sensitive capabilitylinkedin_update_postno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (21 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 |
|---|---|---|---|---|
v0.3.1 latest |
A 98/100 | 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.
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 @ldraney/mcp-linkedin --onlineOther implementations of Linkedin 20
Independent packages implementing the same tool, scanned with the same engine. Compare all 21 side by side →
LinkedIn Ads MCP Server - Campaign entity management and reporting via LinkedIn Marketing API v2
LinkedIn MCP server — publish posts, articles, and media via the LinkedIn API
MCP server for LinkedIn API via HarvestAPI - Returns cleaned data in TOON format for token efficiency
MCP server for LinkedIn — post, comment, react, and manage content via AI agents
MCP server for linkedin API integration
MCP server for posting to LinkedIn via the LinkedIn API using an OAuth access token
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