Безопасен ли Fergus Mcp?
Fergus Mcp — Nerq Trust Score 56.5/100 (Оценка D). Рейтинг основан на 5 independent trust signals.
Fergus Mcp — это software tool с рейтингом доверия Nerq 56.5/100 (D), based on 5 независимых показателей данных. Безопасность: 0/100. Обслуживание: 1/100. Популярность: 0/100. Данные из множественные публичные источники, включая реестры пакетов, GitHub, NVD, OSV.dev и OpenSSF Scorecard. Последнее обновление: n/a. Машинночитаемые данные (JSON).
Безопасен ли Fergus Mcp?
Детали рейтинга доверия — Fergus Mcp has a Nerq Trust Score of 56.5/100 (D). Measured across 5 independent trust signals.
Каков рейтинг доверия Fergus Mcp?
Fergus Mcp имеет Nerq Trust Score 56.5/100 с оценкой D. Этот балл основан на 5 независимо измеренных параметрах, включая безопасность, обслуживание и принятие сообществом.
Каковы основные выводы по безопасности Fergus Mcp?
Самый сильный сигнал Fergus Mcp — соответствие на уровне 87/100. Известных уязвимостей не обнаружено.
Что такое Fergus Mcp и кто его поддерживает?
| Разработчик | Jayco-Design |
| Категория | Infrastructure |
| Источник | https://github.com/Jayco-Design/fergus-mcp |
| Frameworks | anthropic · mcp |
| Protocols | mcp · rest |
Соответствие нормативам
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 87/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Популярные альтернативы в infrastructure
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 безопасность vulnerabilities, обслуживание activity, license соответствие, and принятие сообществом.
How Nerq Assesses Fergus Mcp's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five показателей. Here is how Fergus Mcp performs in each:
- Безопасность (0/100): Fergus Mcp's безопасность posture is poor. This score factors in known CVEs, dependency vulnerabilities, безопасность policy presence, and code signing practices.
- Обслуживание (1/100): Fergus Mcp is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (1/100): Documentation quality is insufficient. This includes README completeness, API документация, usage examples, and contribution guidelines.
- Compliance (87/100): Fergus Mcp is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. На основе GitHub stars, forks, download counts, and ecosystem integrations.
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:
- Developers and teams working with infrastructure tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Fergus Mcp's measured signals (безопасность 0/100, обслуживание 1/100, документация 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:
- Check the source code — Проверьте repository's безопасность policy, open issues, and recent commits for signs of active обслуживание.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Fergus Mcp's dependency tree. - Отзыв permissions — Understand what access Fergus Mcp requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Fergus Mcp in a sandboxed environment before granting access to production data or systems.
- Monitor continuously — Use Nerq's API to set up automated trust checks:
GET nerq.ai/v1/preflight?target=fergus-mcp - Проверьте 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.
- 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 безопасность 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:
Understand how Fergus Mcp processes, stores, and transmits your data. Проверьте tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Fergus Mcp's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher безопасность risk.
Regularly check for updates to Fergus Mcp. Безопасность patches and bug fixes are only effective if you're running the latest version.
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.
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 соответствие assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal соответствие.
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:
Periodically review how Fergus Mcp is used in your workflow. Check for unexpected behavior, permissions drift, and соответствие with your безопасность policies.
Ensure Fergus Mcp and all its dependencies are running the latest stable versions to benefit from безопасность patches.
Grant Fergus Mcp only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Fergus Mcp's безопасность advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
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:
- Environments handling sensitive or regulated data (healthcare, finance, government)
- Mission-critical systems where downtime has significant business impact
- Deployments with strict regulatory requirements that must be independently validated
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 умеренный 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 обслуживание 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 безопасность and quality. Conversely, a downward trend may signal reduced обслуживание, 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 — безопасность, обслуживание, документация, соответствие, and community — has evolved independently, providing granular visibility into which aspects of Fergus Mcp are strengthening or weakening over time.
Fergus Mcp vs Альтернативы
In the infrastructure category, Fergus Mcp scores 56.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Fergus Mcp vs n8n — Trust Score: 69.1/100
- Fergus Mcp vs langflow — Trust Score: 77.0/100
- Fergus Mcp vs dify — Trust Score: 69.7/100
Основные выводы
- Fergus Mcp has a measured Nerq Trust Score of 56.5/100 (D) — a composite of independent signals, not a suitability judgment.
- Among infrastructure tools, Fergus Mcp scores near the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — безопасность, обслуживание, документация, соответствие, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Часто задаваемые вопросы
Безопасен ли Fergus Mcp?
Каков рейтинг доверия Fergus Mcp?
Какие более безопасные альтернативы Fergus Mcp?
Как часто обновляется оценка безопасности Fergus Mcp?
Могу ли я использовать Fergus Mcp в регулируемой среде?
См. также
Disclaimer: Рейтинги доверия Nerq — это автоматические оценки, основанные на публично доступных сигналах. Они не являются рекомендацией или гарантией. Всегда проводите собственную проверку.