¿Es Deepwiki Mcp Seguro?
Deepwiki Mcp — Nerq Trust Score 72.5/100 (Grado B). Basado en el análisis de 4 dimensiones de confianza, se considera generalmente seguro pero con algunas preocupaciones. Última actualización: 2026-07-16.
Sí, Deepwiki Mcp es seguro para usar. Deepwiki Mcp es un software tool (📖 MCP server for fetch deepwiki) con un Nerq Trust Score de 72.5/100 (B), basado en 4 dimensiones de datos independientes. Recomendado para uso. Mantenimiento: 0/100. Popularidad: 1/100. Datos de múltiples fuentes públicas incluyendo registros de paquetes, GitHub, NVD, OSV.dev y OpenSSF Scorecard. Última actualización: 2026-07-16. Datos legibles por máquina (JSON).
¿Es Deepwiki Mcp Seguro?
YES — Deepwiki Mcp has a Nerq Trust Score of 72.5/100 (B). Cumple el umbral de confianza de Nerq con señales fuertes en seguridad, mantenimiento y adopción comunitaria. Recomendado para uso — revise el informe completo a continuación para consideraciones específicas.
¿Cuál es la puntuación de confianza de Deepwiki Mcp?
Deepwiki Mcp tiene una Puntuación de Confianza Nerq de 72.5/100, obteniendo un grado B. Esta puntuación se basa en 4 dimensiones medidas independientemente.
¿Cuáles son los hallazgos de seguridad clave de Deepwiki Mcp?
La señal más fuerte de Deepwiki Mcp es cumplimiento con 100/100. No se han detectado vulnerabilidades conocidas. Cumple con el umbral verificado de Nerq de 70+.
¿Qué es Deepwiki Mcp y quién lo mantiene?
| Autor | regenrek |
| Categoría | Infrastructure |
| Estrellas | 1,259 |
| Fuente | https://github.com/regenrek/deepwiki-mcp |
| Protocols | mcp |
Cumplimiento Regulatorio
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Alternativas Populares en infrastructure
Deepwiki Mcp en Otras Plataformas
Mismo desarrollador/empresa en otros registros:
What Is Deepwiki Mcp?
Deepwiki Mcp is a software tool in the infrastructure category: 📖 MCP server for fetch deepwiki.com and get latest knowledge in Cursor and other Code Editors. It has 1,259 GitHub stars. Nerq Trust Score: 72/100 (B).
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 Deepwiki Mcp's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensiones. Here is how Deepwiki Mcp performs in each:
- Mantenimiento (0/100): Deepwiki Mcp is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (0/100): Documentation quality is insufficient. This includes README completeness, API documentación, usage examples, and contribution guidelines.
- Compliance (100/100): Deepwiki Mcp is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (1/100): Community adoption is limited. Basado en GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 72.5/100 (B) reflects the weighted combination of these signals. This exceeds the Nerq Verified threshold of 70, indicating the tool meets our standards for production use.
Who Should Use Deepwiki Mcp?
Deepwiki Mcp is designed for:
- Developers and teams working with infrastructure tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Deepwiki Mcp meets the minimum threshold for production use, but we recommend monitoring for seguridad advisories and keeping dependencies up to date. Consider implementing additional guardrails for sensitive workloads.
How to Verify Deepwiki 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 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 Deepwiki Mcp's dependency tree. - Reseña permissions — Understand what access Deepwiki Mcp requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Deepwiki 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=deepwiki-mcp - Revisar el/la license — Confirm that Deepwiki 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 Deepwiki Mcp
When evaluating whether Deepwiki Mcp is safe, consider these category-specific risks:
Understand how Deepwiki 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 Deepwiki Mcp's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher seguridad risk.
Regularly check for updates to Deepwiki Mcp. Seguridad patches and bug fixes are only effective if you're running the latest version.
If Deepwiki 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 Deepwiki 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 Deepwiki Mcp in violation of its license can expose your organization to legal liability.
Best Practices for Using Deepwiki Mcp Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Deepwiki Mcp while minimizing risk:
Periodically review how Deepwiki Mcp is used in your workflow. Check for unexpected behavior, permissions drift, and cumplimiento with your seguridad policies.
Ensure Deepwiki Mcp and all its dependencies are running the latest stable versions to benefit from seguridad patches.
Grant Deepwiki Mcp only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Deepwiki 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 Deepwiki Mcp is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Deepwiki Mcp?
Even well-trusted tools aren't right for every situation. Consider avoiding Deepwiki Mcp in these scenarios:
- Scenarios where Deepwiki Mcp's specific capabilities exceed your actual needs — simpler tools may be safer
- Air-gapped environments where the tool cannot receive seguridad updates
- Projects with strict regulatory requirements that haven't been explicitly validated
For each scenario, evaluate whether Deepwiki Mcp's trust score of 72.5/100 meets your organization's risk tolerance. The Nerq Verified status indicates general production readiness, but sector-specific requirements may apply.
How Deepwiki 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. Deepwiki Mcp's score of 72.5/100 is significantly above the category average of 62/100.
This places Deepwiki Mcp in the top tier of infrastructure tools that Nerq tracks. Tools scoring this far above average typically demonstrate mature seguridad practices, consistent release cadence, and broad adopción por la comunidad.
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 Deepwiki 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, Deepwiki 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 Deepwiki Mcp's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=deepwiki-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 Deepwiki Mcp are strengthening or weakening over time.
Deepwiki Mcp vs Alternativas
In the infrastructure category, Deepwiki Mcp scores 72.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Deepwiki Mcp vs langflow — Trust Score: 64.6/100
- Deepwiki Mcp vs dify — Trust Score: 64.0/100
- Deepwiki Mcp vs open-webui — Trust Score: 59.8/100
Puntos Clave
- Deepwiki Mcp has a Trust Score of 72.5/100 (B) and is Nerq Verified.
- Deepwiki Mcp meets the minimum threshold for production deployment, though monitoring and additional guardrails are recommended.
- Among infrastructure tools, Deepwiki Mcp scores significantly above the category average of 62/100, demonstrating above-average reliability.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
Preguntas Frecuentes
¿Es Deepwiki Mcp Seguro?
¿Cuál es la puntuación de confianza de Deepwiki Mcp?
¿Cuáles son alternativas más seguras a Deepwiki Mcp?
¿Con qué frecuencia se actualiza la puntuación de Deepwiki Mcp?
¿Puedo usar Deepwiki 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.