Je Mcp Collection bezpečný?

Mcp Collection — Nerq Trust Score 58.0/100 (Stupeň D). Skóre založeno na 5 independent trust signals.

Mcp Collection je software tool se skóre důvěryhodnosti Nerq 58.0/100 (D), based on 5 nezávislých datových dimenzích. Bezpečnost: 0/100. Údržba: 1/100. Popularita: 0/100. Data pocházejí z více veřejných zdrojů včetně registrů balíčků, GitHubu, NVD, OSV.dev a OpenSSF Scorecard. Naposledy aktualizováno: n/a. Strojově čitelná data (JSON).

Je Mcp Collection bezpečný?

Rozpis skóre důvěryhodnosti — Mcp Collection has a Nerq Trust Score of 58.0/100 (D). Measured across 5 independent trust signals.

Bezpečnostní analýza → Zpráva o soukromí Mcp Collection →

Jaké je skóre důvěryhodnosti Mcp Collection?

Mcp Collection má Nerq skóre důvěryhodnosti 58.0/100 se stupněm D. Toto skóre je založeno na 5 nezávisle měřených dimenzích.

Bezpečnost
0
Shoda
100
Údržba
1
Dokumentace
1
Popularita
0

Jaká jsou klíčová bezpečnostní zjištění pro Mcp Collection?

Nejsilnější signál Mcp Collection je shoda na 100/100. Nebyly zjištěny žádné známé zranitelnosti.

⚠Bezpečnostní skóre: 0/100 (slabý)
⚠Údržba: 1/100 — nízká údržba
⚠Shoda: 100/100 — covers 52 of 52 jurisdictions
⚠Dokumentace: 1/100 — omezená dokumentace
⚠Popularita: 0/100 — 3 hvězdiček na github

Co je Mcp Collection a kdo jej spravuje?

Autorerhardtconsulting
KategorieInfrastructure
Hvězdičky3
Zdrojhttps://github.com/erhardtconsulting/mcp-collection
Frameworksmcp
Protocolsmcp · rest · websocket

Regulační shoda

EU AI Act Risk ClassMINIMAL
Compliance Score100/100
JurisdictionsAssessed across 52 jurisdictions

Populární alternativy v infrastructure

n8n-io/n8n
69.1/100 · C
github
langflow-ai/langflow
77.0/100 · B
github
langgenius/dify
69.7/100 · C
github
open-webui/open-webui
60.4/100 · C
github
google-gemini/gemini-cli
56.2/100 · D
github

What Is Mcp Collection?

Mcp Collection is a software tool in the infrastructure category: Collection of MCP servers with integrated supergateway for Kubernetes-first deployment.. It has 3 GitHub stars. Nerq Trust Score: 58/100 (D).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including bezpečnost vulnerabilities, údržba activity, license shoda, and přijetí komunitou.

How Nerq Assesses Mcp Collection's Safety

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

The overall Trust Score of 58.0/100 (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 Collection?

Mcp Collection is commonly evaluated by:

How to read the signals: Mcp Collection's measured signals (bezpečnost 0/100, údržba 1/100, dokumentace 1/100, community 0/100) 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 Collection's Safety Yourself

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

  1. Check the source code — Zkontrolujte repository's bezpečnost policy, open issues, and recent commits for signs of active údržba.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Mcp Collection's dependency tree.
  3. Recenze permissions — Understand what access Mcp Collection requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Mcp Collection 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-collection
  6. Zkontrolujte license — Confirm that Mcp Collection'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 bezpečnost concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Mcp Collection

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

Data handling

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

Dependency bezpečnost

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

Update frequency

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

Third-party integrations

If Mcp Collection 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 shoda

Verify that Mcp Collection'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 Collection in violation of its license can expose your organization to legal liability.

Mcp Collection and the EU AI Act

Mcp Collection is classified as Minimal Risk under the EU AI Act. This is the lowest risk category, meaning it faces minimal regulatory requirements. However, transparency obligations still apply.

Nerq's shoda assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal shoda.

Best Practices for Using Mcp Collection Safely

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

Conduct regular audits

Periodically review how Mcp Collection is used in your workflow. Check for unexpected behavior, permissions drift, and shoda with your bezpečnost policies.

Keep dependencies updated

Ensure Mcp Collection and all its dependencies are running the latest stable versions to benefit from bezpečnost patches.

Follow least privilege

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

Monitor for bezpečnost advisories

Subscribe to Mcp Collection's bezpečnost 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 Collection is used within your organization, including data handling guidelines and acceptable use cases.

Situations That Warrant Independent Review of Mcp Collection

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

For each situation, compare Mcp Collection's measured trust score of 58.0/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Mcp Collection is suitable for any particular use.

How Mcp Collection Compares to Industry Standards

Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among infrastructure tools, the average Trust Score is 62/100. Mcp Collection's score of 58.0/100 is near the category average of 62/100.

This places Mcp Collection in line with the typical infrastructure 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 střední 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 Collection 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 údržba patterns change, Mcp Collection'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 bezpečnost and quality. Conversely, a downward trend may signal reduced údržba, growing technical debt, or unresolved vulnerabilities. To track Mcp Collection's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=mcp-collection&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 — bezpečnost, údržba, dokumentace, shoda, and community — has evolved independently, providing granular visibility into which aspects of Mcp Collection are strengthening or weakening over time.

Mcp Collection vs Alternativy

In the infrastructure category, Mcp Collection scores 58.0/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Hlavní závěry

Často kladené otázky

Je Mcp Collection bezpečný?
mcp-collection se skóre důvěryhodnosti Nerq 58.0/100 (D). Nejsilnější signál: shoda (100/100). Skóre založeno na Bezpečnost (0/100), Údržba (1/100), Popularita (0/100), Dokumentace (1/100).
Jaké je skóre důvěryhodnosti Mcp Collection?
mcp-collection: 58.0/100 (D). Skóre založeno na Bezpečnost (0/100), Údržba (1/100), Popularita (0/100), Dokumentace (1/100). Compliance: 100/100. Skóre se aktualizují, jakmile jsou k dispozici nová data. API: GET nerq.ai/v1/preflight?target=mcp-collection
Jaké jsou bezpečnější alternativy k Mcp Collection?
V kategorii Infrastructure, higher-rated alternatives include n8n-io/n8n (69/100), langflow-ai/langflow (77/100), langgenius/dify (70/100). mcp-collection scores 58.0/100.
Jak často se aktualizuje bezpečnostní skóre Mcp Collection?
Nerq recomputes Mcp Collection's trust score as new data becomes available. Current: 58.0/100 (D). API: GET nerq.ai/v1/preflight?target=mcp-collection
Mohu používat Mcp Collection v regulovaném prostředí?
Mcp Collection: 58.0/100 (D). Compliance: 52 of 52 jurisdictions. EU AI Act compliant. Evaluate against your own regulatory requirements.
API: /v1/preflight Trust Badge API Docs

Viz také

Disclaimer: Skóre důvěryhodnosti Nerq jsou automatizovaná hodnocení založená na veřejně dostupných signálech. Nejsou doporučením ani zárukou. Vždy proveďte vlastní ověření.

Používáme cookies pro analýzu a ukládání do mezipaměti. Soukromí