¿Es Serverless Mcp Seguro?
Serverless Mcp — Nerq Trust Score 55.3/100 (Grado D). Puntuación basada en 5 independent trust signals.
Serverless Mcp es un software tool con un Nerq Trust Score de 55.3/100 (D), basado en 5 dimensiones de datos independientes. Seguridad: 0/100. Mantenimiento: 1/100. Popularidad: 0/100. Datos de múltiples fuentes públicas incluyendo registros de paquetes, GitHub, NVD, OSV.dev y OpenSSF Scorecard. Última actualización: n/a. Datos legibles por máquina (JSON).
¿Es Serverless Mcp Seguro?
Desglose de Puntuación de Confianza — Serverless Mcp has a Nerq Trust Score of 55.3/100 (D). Measured across 5 independent trust signals.
¿Cuál es la puntuación de confianza de Serverless Mcp?
Serverless Mcp tiene una Puntuación de Confianza Nerq de 55.3/100, obteniendo un grado D. Esta puntuación se basa en 5 dimensiones medidas independientemente.
¿Cuáles son los hallazgos de seguridad clave de Serverless Mcp?
La señal más fuerte de Serverless Mcp es cumplimiento con 100/100. No se han detectado vulnerabilidades conocidas.
¿Qué es Serverless Mcp y quién lo mantiene?
| Autor | geoicons |
| Categoría | Infrastructure |
| Fuente | https://github.com/geoicons/serverless-mcp |
| Frameworks | mcp |
| Protocols | mcp · rest |
Cumplimiento Regulatorio
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Alternativas Populares en infrastructure
What Is Serverless Mcp?
Serverless Mcp is a software tool in the infrastructure category: Node JS backed AWS Serverless MCP Server. Nerq Trust Score: 55/100 (D).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including seguridad vulnerabilities, mantenimiento activity, license cumplimiento, and adopción por la comunidad.
How Nerq Assesses Serverless Mcp's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensiones. Here is how Serverless Mcp performs in each:
- Seguridad (0/100): Serverless Mcp's seguridad posture is poor. This score factors in known CVEs, dependency vulnerabilities, seguridad policy presence, and code signing practices.
- Mantenimiento (1/100): Serverless 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 documentación, usage examples, and contribution guidelines.
- Compliance (100/100): Serverless 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. Basado en GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 55.3/100 (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 Serverless Mcp?
Serverless 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: Serverless Mcp's measured signals (seguridad 0/100, mantenimiento 1/100, documentación 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 Serverless Mcp's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Revisar el/la repository's seguridad policy, open issues, and recent commits for signs of active mantenimiento.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Serverless Mcp's dependency tree. - Reseña permissions — Understand what access Serverless Mcp requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Serverless 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=serverless-mcp - Revisar el/la license — Confirm that Serverless 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 seguridad concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Serverless Mcp
When evaluating whether Serverless Mcp is safe, consider these category-specific risks:
Understand how Serverless Mcp processes, stores, and transmits your data. Revisar el/la tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Serverless Mcp's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher seguridad risk.
Regularly check for updates to Serverless Mcp. Seguridad patches and bug fixes are only effective if you're running the latest version.
If Serverless 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 Serverless 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 Serverless Mcp in violation of its license can expose your organization to legal liability.
Serverless Mcp and the EU AI Act
Serverless 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 cumplimiento assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal cumplimiento.
Best Practices for Using Serverless Mcp Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Serverless Mcp while minimizing risk:
Periodically review how Serverless Mcp is used in your workflow. Check for unexpected behavior, permissions drift, and cumplimiento with your seguridad policies.
Ensure Serverless Mcp and all its dependencies are running the latest stable versions to benefit from seguridad patches.
Grant Serverless Mcp only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Serverless Mcp's seguridad advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Serverless Mcp is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Serverless Mcp
Nerq's signals are one input. In the following situations, evaluate Serverless 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 Serverless Mcp's measured trust score of 55.3/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Serverless Mcp is suitable for any particular use.
How Serverless 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. Serverless Mcp's score of 55.3/100 is near the category average of 62/100.
This places Serverless 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 moderado 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 Serverless 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 mantenimiento patterns change, Serverless 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 seguridad and quality. Conversely, a downward trend may signal reduced mantenimiento, growing technical debt, or unresolved vulnerabilities. To track Serverless Mcp's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=serverless-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 — seguridad, mantenimiento, documentación, cumplimiento, and community — has evolved independently, providing granular visibility into which aspects of Serverless Mcp are strengthening or weakening over time.
Serverless Mcp vs Alternativas
In the infrastructure category, Serverless Mcp scores 55.3/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Serverless Mcp vs n8n — Trust Score: 69.1/100
- Serverless Mcp vs langflow — Trust Score: 77.0/100
- Serverless Mcp vs dify — Trust Score: 69.7/100
Puntos Clave
- Serverless Mcp has a measured Nerq Trust Score of 55.3/100 (D) — a composite of independent signals, not a suitability judgment.
- Among infrastructure tools, Serverless Mcp scores near the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — seguridad, mantenimiento, documentación, cumplimiento, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Preguntas Frecuentes
¿Es Serverless Mcp Seguro?
¿Cuál es la puntuación de confianza de Serverless Mcp?
¿Cuáles son alternativas más seguras a Serverless Mcp?
¿Con qué frecuencia se actualiza la puntuación de Serverless Mcp?
¿Puedo usar Serverless Mcp en un entorno regulado?
Ver también
Disclaimer: Las puntuaciones de confianza de Nerq son evaluaciones automatizadas basadas en señales disponibles públicamente. No son respaldos ni garantías. Siempre realice su propia diligencia debida.