Is Mcp Skill Server veilig?

Mcp Skill Server — Nerq Trust Score 52.8/100 (D-beoordeling). Score gebaseerd op 1 independent trust signals.

Mcp Skill Server is een software tool met een Nerq Vertrouwensscore van 52.8/100 (D), based on 3 onafhankelijke gegevensdimensies. Gegevens afkomstig van meerdere openbare bronnen waaronder pakketregisters, GitHub, NVD, OSV.dev en OpenSSF Scorecard. Laatst bijgewerkt: n/a. Machineleesbare gegevens (JSON).

Is Mcp Skill Server veilig?

Vertrouwensscore details — Mcp Skill Server has a Nerq Trust Score of 52.8/100 (D). Measured across 1 independent trust signal.

Beveiligingsanalyse → Mcp Skill Server Privacyrapport →

Wat is de vertrouwensscore van Mcp Skill Server?

Mcp Skill Server heeft een Nerq Trust Score van 52.8/100 met het cijfer D. Deze score is gebaseerd op 1 onafhankelijk gemeten dimensies, waaronder beveiliging, onderhoud en community-adoptie.

Naleving
100

Wat zijn de belangrijkste beveiligingsbevindingen voor Mcp Skill Server?

Het sterkste signaal van Mcp Skill Server is naleving met 100/100. Er zijn geen bekende kwetsbaarheden gedetecteerd.

⚠Naleving: 100/100 — covers 52 of 52 jurisdicties

Wat is Mcp Skill Server en wie onderhoudt het?

OntwikkelaarJanine Cheng
CategorieUncategorized
Bronhttps://pypi.org/project/mcp-skill-server/

Naleving van regelgeving

EU AI Act Risk ClassNot assessed
Compliance Score100/100
JurisdictionsAssessed across 52 jurisdicties

What Is Mcp Skill Server?

Mcp Skill Server is a software tool in the uncategorized category: Develop AI skills locally in your editor, deploy to production when ready. Nerq Trust Score: 53/100 (D).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including beveiliging vulnerabilities, onderhoud activity, license naleving, and gemeenschapsacceptatie.

How Nerq Assesses Mcp Skill Server's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensies. Here is how Mcp Skill Server performs in each:

The overall Trust Score of 52.8/100 (D) is the weighted combination of these measured signals. It is a measurement, not a pass/fail or suitability judgment — weigh the individual signals against your own requirements.

Who Typically Evaluates Mcp Skill Server?

Mcp Skill Server is commonly evaluated by:

How to read the signals: Mcp Skill Server's measured signals (the trust signals above) are shown above. These are measurements, not a suitability judgment — weigh each signal against the requirements of your own use case and risk tolerance.

How to Verify Mcp Skill Server's Safety Yourself

While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:

  1. Check the source code — Bekijk de repository beveiliging policy, open issues, and recent commits for signs of active onderhoud.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Mcp Skill Server's dependency tree.
  3. Beoordeling permissions — Understand what access Mcp Skill Server requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Mcp Skill Server in a sandboxed environment before granting access to production data or systems.
  5. Monitor continuously — Use Nerq's API to set up automated trust checks: GET nerq.ai/v1/preflight?target=mcp-skill-server
  6. Bekijk de license — Confirm that Mcp Skill Server's license is compatible with your intended use case. Pay attention to restrictions on commercial use, redistribution, and derivative works. Some AI tools use dual licensing or have separate terms for enterprise customers that differ from the open-source license.
  7. Check community signals — Look at the project's issue tracker, discussion forums, and social media presence. A healthy community actively reports bugs, contributes fixes, and discusses beveiliging concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Mcp Skill Server

When evaluating whether Mcp Skill Server is safe, consider these category-specific risks:

Data handling

Understand how Mcp Skill Server processes, stores, and transmits your data. Bekijk de tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency beveiliging

Check Mcp Skill Server's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher beveiliging risk.

Update frequency

Regularly check for updates to Mcp Skill Server. Beveiliging patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Mcp Skill Server connects to external APIs or services, each integration point is a potential attack surface. Audit all third-party connections, verify that data shared with external services is minimized, and ensure that integration credentials are rotated regularly.

License and IP naleving

Verify that Mcp Skill Server's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Mcp Skill Server in violation of its license can expose your organization to legal liability.

Best Practices for Using Mcp Skill Server Safely

Whether you're an individual developer or an enterprise team, these practices will help you get the most from Mcp Skill Server while minimizing risk:

Conduct regular audits

Periodically review how Mcp Skill Server is used in your workflow. Check for unexpected behavior, permissions drift, and naleving with your beveiliging policies.

Keep dependencies updated

Ensure Mcp Skill Server and all its dependencies are running the latest stable versions to benefit from beveiliging patches.

Follow least privilege

Grant Mcp Skill Server only the minimum permissions it needs to function. Avoid granting admin or root access.

Monitor for beveiliging advisories

Subscribe to Mcp Skill Server's beveiliging advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.

Document usage policies

Create and maintain a clear policy for how Mcp Skill Server is used within your organization, including data handling guidelines and acceptable use cases.

Situations That Warrant Independent Review of Mcp Skill Server

Nerq's signals are one input. In the following situations, evaluate Mcp Skill Server's measured signals against your own requirements before making a decision:

For each situation, compare Mcp Skill Server's measured trust score of 52.8/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Mcp Skill Server is suitable for any particular use.

How Mcp Skill Server Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among uncategorized tools, the average Trust Score is 62/100. Mcp Skill Server's score of 52.8/100 is near the category average of 62/100.

This places Mcp Skill Server in line with the typical uncategorized tool tool. It meets baseline expectations but does not distinguish itself from peers on trust metrics.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks matig in isolation may actually represent strong performance within a challenging category — or vice versa. Nerq's category-relative analysis helps teams make informed decisions by showing not just absolute quality, but how a tool ranks against its direct peers.

Trust Score History

Nerq continuously monitors Mcp Skill Server and recalculates its Trust Score as new data becomes available. Our scoring engine ingests real-time signals from source repositories, vulnerability databases (NVD, OSV.dev), package registries, and community metrics. When a new CVE is published, a major release ships, or onderhoud patterns change, Mcp Skill Server's score is updated within 24 hours.

Historical trust trends reveal whether a tool is improving, stable, or declining over time. A tool that consistently maintains or improves its score demonstrates ongoing commitment to beveiliging and quality. Conversely, a downward trend may signal reduced onderhoud, growing technical debt, or unresolved vulnerabilities. To track Mcp Skill Server's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=mcp-skill-server&include=history

Nerq retains trust score snapshots at regular intervals, enabling trend analysis across weeks and months. Enterprise users can access detailed historical reports showing how each dimension — beveiliging, onderhoud, documentatie, naleving, and community — has evolved independently, providing granular visibility into which aspects of Mcp Skill Server are strengthening or weakening over time.

Belangrijkste conclusies

Veelgestelde vragen

Is Mcp Skill Server veilig?
mcp-skill-server met een Nerq Vertrouwensscore van 52.8/100 (D). Sterkste signaal: naleving (100/100). Score gebaseerd op multiple trust dimensies.
Wat is de vertrouwensscore van Mcp Skill Server?
mcp-skill-server: 52.8/100 (D). Score gebaseerd op multiple trust dimensies. Compliance: 100/100. Scores worden bijgewerkt wanneer nieuwe data beschikbaar komen. API: GET nerq.ai/v1/preflight?target=mcp-skill-server
Wat zijn veiligere alternatieven voor Mcp Skill Server?
In de categorie Uncategorized, meer software tool worden geanalyseerd — kom binnenkort terug. mcp-skill-server scores 52.8/100.
Hoe vaak wordt de beveiligingsscore van Mcp Skill Server bijgewerkt?
Nerq recomputes Mcp Skill Server's trust score as new data becomes available. Current: 52.8/100 (D). API: GET nerq.ai/v1/preflight?target=mcp-skill-server
Kan ik Mcp Skill Server gebruiken in een gereguleerde omgeving?
Mcp Skill Server: 52.8/100 (D). Compliance: 52 of 52 jurisdicties. Evaluate against your own regulatory requirements.
API: /v1/preflight Trust Badge API Docs

Zie ook

Disclaimer: Nerq-vertrouwensscores zijn geautomatiseerde beoordelingen op basis van openbaar beschikbare signalen. Ze vormen geen aanbeveling of garantie. Voer altijd uw eigen verificatie uit.

We gebruiken cookies voor analyse en caching. Privacy