Apakah Fergus Mcp Aman?

Fergus Mcp — Nerq Trust Score 56.5/100 (Nilai D). Skor berdasarkan 5 independent trust signals.

Fergus Mcp adalah software tool dengan Skor Kepercayaan Nerq sebesar 56.5/100 (D), based on 5 dimensi data independen. Keamanan: 0/100. Pemeliharaan: 1/100. Popularitas: 0/100. Data bersumber dari berbagai sumber publik termasuk registri paket, GitHub, NVD, OSV.dev, dan OpenSSF Scorecard. Terakhir diperbarui: n/a. Data yang dapat dibaca mesin (JSON).

Apakah Fergus Mcp Aman?

Rincian Skor Kepercayaan — Fergus Mcp has a Nerq Trust Score of 56.5/100 (D). Measured across 5 independent trust signals.

Analisis Keamanan → Laporan Privasi Fergus Mcp →

Berapa skor kepercayaan Fergus Mcp?

Fergus Mcp memiliki Skor Kepercayaan Nerq 56.5/100 dengan nilai D. Skor ini didasarkan pada 5 dimensi yang diukur secara independen.

Keamanan
0
Kepatuhan
87
Pemeliharaan
1
Dokumentasi
1
Popularitas
0

Apa temuan keamanan utama untuk Fergus Mcp?

Sinyal terkuat Fergus Mcp adalah kepatuhan pada 87/100. Tidak ada kerentanan yang diketahui terdeteksi.

⚠Skor keamanan: 0/100 (lemah)
⚠Pemeliharaan: 1/100 — aktivitas pemeliharaan rendah
⚠Kepatuhan: 87/100 — covers 45 of 52 jurisdictions
⚠Dokumentasi: 1/100 — dokumentasi terbatas
⚠Popularitas: 0/100 — adopsi komunitas

Apa itu Fergus Mcp dan siapa yang mengelolanya?

PembuatJayco-Design
KategoriInfrastructure
Sumberhttps://github.com/Jayco-Design/fergus-mcp
Frameworksanthropic · mcp
Protocolsmcp · rest

Kepatuhan Regulasi

EU AI Act Risk ClassMINIMAL
Compliance Score87/100
JurisdictionsAssessed across 52 jurisdictions

Alternatif Populer di 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 Fergus Mcp?

Fergus Mcp is a software tool in the infrastructure category: Fergus MCP Server for AI integrates with Fergus API to manage AI assistant interactions.. Nerq Trust Score: 56/100 (D).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including keamanan vulnerabilities, pemeliharaan activity, license kepatuhan, and adopsi komunitas.

How Nerq Assesses Fergus Mcp's Safety

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

The overall Trust Score of 56.5/100 (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 Fergus Mcp?

Fergus Mcp is commonly evaluated by:

How to read the signals: Fergus Mcp's measured signals (keamanan 0/100, pemeliharaan 1/100, dokumentasi 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 Fergus Mcp's Safety Yourself

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

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

Common Safety Concerns with Fergus Mcp

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

Data handling

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

Dependency keamanan

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

Update frequency

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

Third-party integrations

If Fergus Mcp 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 kepatuhan

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

Fergus Mcp and the EU AI Act

Fergus Mcp 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 kepatuhan assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal kepatuhan.

Best Practices for Using Fergus Mcp Safely

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

Conduct regular audits

Periodically review how Fergus Mcp is used in your workflow. Check for unexpected behavior, permissions drift, and kepatuhan with your keamanan policies.

Keep dependencies updated

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

Follow least privilege

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

Monitor for keamanan advisories

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

Situations That Warrant Independent Review of Fergus Mcp

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

For each situation, compare Fergus Mcp's measured trust score of 56.5/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Fergus Mcp is suitable for any particular use.

How Fergus Mcp 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. Fergus Mcp's score of 56.5/100 is near the category average of 62/100.

This places Fergus Mcp 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 sedang 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 Fergus Mcp 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 pemeliharaan patterns change, Fergus Mcp'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 keamanan and quality. Conversely, a downward trend may signal reduced pemeliharaan, growing technical debt, or unresolved vulnerabilities. To track Fergus Mcp's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=fergus-mcp&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 — keamanan, pemeliharaan, dokumentasi, kepatuhan, and community — has evolved independently, providing granular visibility into which aspects of Fergus Mcp are strengthening or weakening over time.

Fergus Mcp vs Alternatif

In the infrastructure category, Fergus Mcp scores 56.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Kesimpulan Utama

Pertanyaan yang Sering Diajukan

Apakah Fergus Mcp Aman?
fergus-mcp dengan Skor Kepercayaan Nerq sebesar 56.5/100 (D). Sinyal terkuat: kepatuhan (87/100). Skor berdasarkan Keamanan (0/100), Pemeliharaan (1/100), Popularitas (0/100), Dokumentasi (1/100).
Berapa skor kepercayaan Fergus Mcp?
fergus-mcp: 56.5/100 (D). Skor berdasarkan Keamanan (0/100), Pemeliharaan (1/100), Popularitas (0/100), Dokumentasi (1/100). Compliance: 87/100. Skor diperbarui saat data baru tersedia. API: GET nerq.ai/v1/preflight?target=fergus-mcp
Apa alternatif yang lebih aman dari Fergus Mcp?
Dalam kategori Infrastructure, higher-rated alternatives include n8n-io/n8n (69/100), langflow-ai/langflow (77/100), langgenius/dify (70/100). fergus-mcp scores 56.5/100.
Seberapa sering skor keamanan Fergus Mcp diperbarui?
Nerq recomputes Fergus Mcp's trust score as new data becomes available. Current: 56.5/100 (D). API: GET nerq.ai/v1/preflight?target=fergus-mcp
Bisakah saya menggunakan Fergus Mcp di lingkungan yang diatur?
Fergus Mcp: 56.5/100 (D). Compliance: 45 of 52 jurisdictions. EU AI Act compliant. Evaluate against your own regulatory requirements.
API: /v1/preflight Trust Badge API Docs

Lihat juga

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