Is LinkedIn MCP Server safe to use?

LinkedIn MCP Server has an HVTrust score of 89.1/100 (Grade A), ranked #28 of 1325 tracked AI agent projects. This score reflects verifiable supply-chain integrity, transparency, maintenance, and adoption signals.

What is the trust score for LinkedIn MCP Server?

LinkedIn MCP Server scores 89.1/100 on HVTracker's evidence-weighted HVTrust scale. It has 3.6k GitHub stars and is categorized under MCP Servers.

LinkedIn MCP Server

stickerdaniel/linkedin-mcp-server

Open-source MCP server for LinkedIn. Give Claude and any MCP-compatible AI agent access to profiles, companies, jobs, and messages.

MCP Servers Python Listed Apache-2.0

Is LinkedIn MCP Server safe? Strong public trust posture, backed by multiple independent signals.

OSSF Scorecard 5.7 / 10

Provenance Attested

Signed commits 95%

Last push today

Compare LinkedIn MCP Server

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In detail: LinkedIn MCP Server scores 89.1/100 (Grade A), ranked #28 of 1325 tracked open-source AI agent projects, on evidence coverage B (3 of 5 independent signal types). The public evidence: its packages ship with cryptographic provenance; OSSF Scorecard rates its supply-chain practices 5.7/10; 95% of recent commits are signed; last pushed 2026-09-27. Every point is earned from checkable signals — never paid placement. How scoring works →

How LinkedIn MCP Server compares in MCP Servers

Bars show each HVTrust score; the tick marks LinkedIn MCP Server’s 89.1.

Where the 89.1 comes from

HVTrust dimensions vs the MCP Servers average

89.1 / 100 · 100.0% confidence

LinkedIn MCP Server MCP Servers average (775 agents)

Safety / Integrity50% OSSF Scorecard · 30% provenance · 20% signed commits

19.4 / 25

9.1 above avg 10.3

Identity / Provenance60% listing status · 40% build provenance

18.0 / 18

4.6 above avg 13.4

Transparency50% declared license · 50% OSSF Scorecard

13.3 / 17

1.1 above avg 12.2

Maintenance60% last-push freshness · 40% commit activity

20.0 / 20

8.0 above avg 12.0

AdoptionLog-scaled stars · package downloads

14.2 / 20

6.9 above avg 7.3

Quick Trust Read

What Would Improve It

Improve adoption to lift the weakest part of the trust profile.

Recent Changes

2026-09-24

Tool Surface Changed

Detected tool/plugin surface changed: none → declared

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → implemented

2026-09-23

Provenance Added

Package provenance attestation detected

Maintainer Checklist

Raise Scorecard signals Current OSSF Scorecard is 5.7/10. Tighten the weakest checks to improve public safety evidence.

Compare with Codebase Memory MCP Get email alerts for LinkedIn MCP Server View MCP Servers Report missing data

84.4

Activity sub-score · out of 100

In MCP Servers

How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade A reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage B is separate — it grades how many independent signal types back the score (3 of 5), so a high score on thin evidence stays visible. Full methodology →

Rank Trend

2026-08-11 2026-09-27

Activity & Reach

Stars

3.6k

Forks

633

Last Push

2026-09-27

today

Commits (4 wk)

182

Downloads (7d)

16,813

pypi

HN mentions (30d)

—

Open Issues

Rank Change

▲1

was #29

Analysis

Activity Inputs

84.4 / 100

StarsRepository reach

21.4 / 30

FreshnessLast push recency

25.0 / 25

ActivityRecent commits

25 / 25

CommunityFork signal

13.0 / 20

Supply Chain Trust

Package Provenance

Verified

pypi attestation

OSSF Scorecard

5.7 / 10

OpenSSF Scorecard · scanned Sep 26, 2026

Signed Commits

95%

of last 100 commits verified

Binary-Artifacts 10

Branch-Protection 3

CI-Tests 10

CII-Best-Practices 0

Code-Review 2

Contributors 3

Dangerous-Workflow 10

Dependency-Update-Tool 10

Fuzzing 0

License 10

Maintained 10

Packaging 10

Pinned-Dependencies 10

SAST 0

Security-Policy 0

Signed-Releases 0

Token-Permissions 0

Vulnerabilities 10

Common questions about LinkedIn MCP Server

Public supply-chain signals for LinkedIn MCP Server are strong: it has multiple independent trust indicators in place. This does not replace your own security review, but LinkedIn MCP Server carries less obvious unverified-evidence risk than projects with thin signals.

Does LinkedIn MCP Server publish package provenance?

Yes. LinkedIn MCP Server's package releases carry build provenance attestations, which cryptographically link the published package back to its source repository and CI workflow.

Does LinkedIn MCP Server have an OpenSSF Scorecard?

LinkedIn MCP Server has an OpenSSF Scorecard score of 5.7/10. The Scorecard checks for branch protection, signed releases, dependency updates, fuzzing, code review, and other supply-chain hygiene items. See the full check breakdown on this page.

Is LinkedIn MCP Server actively maintained?

Actively maintained. The repository was pushed to within the last 1 day(s).

What license does LinkedIn MCP Server use?

LinkedIn MCP Server ships under Apache-2.0. A declared, OSI-approved license is one of the transparency signals HVTrust scores.

Are LinkedIn MCP Server's commits signed?

95% of the last 100 commits to LinkedIn MCP Server are verified-signed (GPG, SSH, S/MIME, or GitHub's signing flow). Signed commits help confirm that code was authored by who the commit claims.

Not a safety endorsement. HVTracker describes what public signals show, not whether a project is safe for your use case. Run your own security review before adopting in production.

Compare LinkedIn MCP Server head-to-head

LinkedIn MCP Server vs Codebase Memory MCP → LinkedIn MCP Server vs Mobile MCP → LinkedIn MCP Server vs Playwright MCP →

AI agent surface

MCP, providers, tool surface

Scored in HVTrust

These runtime-trust fields — detected from public repo docs and manifests — contribute a bounded adjustment to this project's HVTrust score alongside supply-chain evidence. The exact values each field can add or subtract are documented in the methodology → Compare this surface across every listed agent in the capability matrix →

MCP Server Support

high confidence

Implemented

LinkedIn MCP Server appears to expose MCP server capabilities.

Detailed evidence is not shown in the public view.

External Service Dependencies

None detected

No clear third-party provider dependency detected.

Credential signal: No explicit API-key/config marker detected.

Tool / Plugin Surface

high confidence

Declared

Declared plugin/integration surface detected.

Detailed evidence is not shown in the public view.

Package Provenance Drift

high confidence

Match

Published package metadata matches the tracked repo

Detailed evidence is not shown in the public view.

MCP signal live
External deps live
Tool / plugin surface live
Package provenance drift live

How this surface has changed

Detected changes to LinkedIn MCP Server's runtime surface and supply-chain posture, from daily public-signal snapshots. A change here means our detectors see something different — a genuinely changed capability, or better evidence of an existing one.

2026-09-24

Tool Surface Changed

Detected tool/plugin surface changed: none → declared

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → implemented

2026-09-23

Provenance Added

Package provenance attestation detected

2026-09-07

Tool Surface Changed

Detected tool/plugin surface changed: none → declared

2026-09-03

Tool Surface Changed

Detected tool/plugin surface changed: extension-based → none

2026-09-03

Provider Removed

Runtime surface shrank — no longer detected: Anthropic

Maintain LinkedIn MCP Server?

For maintainers

HVTrust scores LinkedIn MCP Server from public signals only — we never contact maintainers first. If a signal is wrong, stale, or missing (provenance you publish, a Scorecard you run, signed releases), tell us and we'll review it. Corrections are public and tracked on GitHub.

Submit a correction → Add the trust badge

Reputation Timeline

Signal history

2026-09-24

Tool Surface Changed

Detected tool/plugin surface changed: none → declared

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → implemented

2026-09-23

Provenance Added

Package provenance attestation detected

2026-09-23

Grade Changed

Trust grade D → A

2026-09-23

Rank Moved

Rank rose 571 spots (#595 → #24)

2026-09-23

HVTrust Changed

HVTrust up 55.2pts (34.1 → 89.3)

2026-09-22

Newly Listed

First tracked at rank #595

2026-09-21

Removed From Active Tracking

Removed from active tracking

2026-09-17

Rank Moved

Rank rose 11 spots (#38 → #27)

2026-09-07

Tool Surface Changed

Detected tool/plugin surface changed: none → declared

2026-09-03

Tool Surface Changed

Detected tool/plugin surface changed: extension-based → none

2026-09-03

Provider Removed

Runtime surface shrank — no longer detected: Anthropic

2026-08-26

Scorecard Added

OSSF Scorecard: 4.9/10

2026-08-26

Grade Changed

Trust grade B → A

2026-08-26

Rank Moved

Rank rose 49 spots (#82 → #33)

2026-08-26

HVTrust Changed

HVTrust up 9.8pts (77.1 → 86.9)

2026-08-10

Newly Listed

First tracked at rank #77

GitHub → PyPI: mcp-server-linkedin

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For maintainers

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Other agents in MCP Servers

Data sources
GitHub REST API (repo, commits, stars, forks, license) · PyPI / pypistats (downloads, provenance) · OpenSSF Scorecard CLI
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.3 · Raw JSON