هل Deepwiki Mcp آمن؟

Deepwiki Mcp — Nerq درجة الثقة 72.5/100 (الدرجة B). بناءً على تحليل 4 أبعاد للثقة، يُعتبر آمنًا بشكل عام مع بعض المخاوف. آخر تحديث: 2026-07-17.

نعم، Deepwiki Mcp آمن للاستخدام. Deepwiki Mcp هو software tool (📖 MCP server for fetch deepwiki) بدرجة ثقة Nerq 72.5/100 (B), بناءً على 4 أبعاد بيانات مستقلة. موصى به للاستخدام. الصيانة: 0/100. الشعبية: 1/100. البيانات مصدرها قراءة آلية.

هل Deepwiki Mcp آمن؟

YES — Deepwiki Mcp لديه درجة ثقة Nerq تبلغ 72.5/100 (B). يستوفي عتبة ثقة Nerq مع إشارات قوية عبر الأمان والصيانة واعتماد المجتمع. موصى به للاستخدام — review the full report below for specific considerations.

تحليل الأمان → تقرير الخصوصية →

ما هي درجة ثقة Deepwiki Mcp؟

حصل Deepwiki Mcp على درجة ثقة Nerq تبلغ 72.5/100 بدرجة B. يعتمد هذا التقييم على 4 أبعاد مُقاسة بشكل مستقل.

الامتثال
100
الصيانة
0
التوثيق
0
الشعبية
1

ما هي النتائج الأمنية الرئيسية لـ Deepwiki Mcp؟

أقوى إشارة لـ Deepwiki Mcp هي الامتثال بدرجة 100/100. لم يتم اكتشاف أي ثغرات أمنية معروفة. يستوفي عتبة التحقق من Nerq البالغة 70+.

الصيانة: 0/100 — نشاط صيانة منخفض
الامتثال: 100/100 — covers 52 of 52 ولاية قضائيةs
التوثيق: 0/100 — توثيق محدود
الشعبية: 1/100 — 1,259 stars on mcp registry

ما هو Deepwiki Mcp ومن يديره؟

المؤلفregenrek
الفئةالبنية التحتية
النجوم1,259
المصدرhttps://github.com/regenrek/deepwiki-mcp
Protocolsmcp

الامتثال التنظيمي

EU AI Act Risk ClassNot assessed
Compliance Score100/100
الاختصاص القضائيsAssessed across 52 ولاية قضائيةs

بدائل شائعة في infrastructure

langflow-ai/langflow
64.6/100 · C+
github
langgenius/dify
64.0/100 · C+
github
open-webui/open-webui
59.8/100 · C
github
google-gemini/gemini-cli
71.8/100 · B
github
supabase/supabase
57.8/100 · C
github

Deepwiki Mcp عبر المنصات

منتجات من نفس المطور

@browser-echo/vite
56/100 · npm
mcp-deepwiki
48/100 · npm
codefetch
48/100 · npm
@browser-echo/next
48/100 · npm
viber3d
48/100 · npm

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 درجة الثقة: 72/100 (B).

Nerq independently analyzes every software tool, app, and extension across multiple trust signals including security vulnerabilities, maintenance activity, license compliance, and اعتماد المجتمع.

How Nerq Assesses Deepwiki Mcp's Safety

Nerq's درجة الثقة is calculated from 13+ independent signals aggregated into five أبعاد. Here is how Deepwiki Mcp performs in each:

The overall درجة الثقة 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:

Risk guidance: Deepwiki Mcp meets the minimum threshold for production use, but we recommend monitoring for security advisories and keeping dependencies up to date. Consider implementing additional guardrails for sensitive workloads.

كيفية Verify Deepwiki 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 — Review the repository security policy, open issues, and recent commits for signs of active maintenance.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for ثغرات أمنية معروفة in Deepwiki Mcp's dependency tree.
  3. مراجعة permissions — Understand what access Deepwiki Mcp requires. Software tools should follow the principle of least privilege.
  4. Test in isolation — Run Deepwiki 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=deepwiki-mcp
  6. مراجعة the 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 عملاء 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 security 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:

Data handling

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

Dependency security

Check Deepwiki Mcp's dependency tree for ثغرات أمنية معروفة. Tools with outdated or unmaintained dependencies pose a higher security risk.

Update frequency

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

Third-party integrations

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.

الترخيص and IP compliance

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:

Conduct regular audits

Periodically review how Deepwiki Mcp is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.

Keep dependencies updated

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

Follow least privilege

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

Monitor for security advisories

Subscribe to Deepwiki Mcp's security 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 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:

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 درجة الثقة 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 security practices, consistent release cadence, and broad اعتماد المجتمع.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks متوسط 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.

درجة الثقة History

Nerq continuously monitors Deepwiki Mcp and recalculates its درجة الثقة 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 maintenance 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 security and quality. Conversely, a downward trend may signal reduced maintenance, 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 — security, maintenance, documentation, compliance, and community — has evolved independently, providing granular visibility into which aspects of Deepwiki Mcp are strengthening or weakening over time.

Deepwiki Mcp vs البدائل

In the infrastructure category, Deepwiki Mcp scores 72.5/100. There are higher-scoring alternatives available. For a detailed comparison, see:

النقاط الرئيسية

الأسئلة الشائعة

هل Deepwiki Mcp آمن؟
نعم، هو آمن للاستخدام. deepwiki-mcp بدرجة ثقة Nerq 72.5/100 (B). أقوى إشارة: الامتثال (100/100). التقييم مبني على الصيانة (0/100), الشعبية (1/100), التوثيق (0/100).
ما هي درجة ثقة Deepwiki Mcp؟
deepwiki-mcp: 72.5/100 (B). التقييم مبني على الصيانة (0/100), الشعبية (1/100), التوثيق (0/100). Compliance: 100/100. يتم تحديث النتائج عند توفر بيانات جديدة. API: GET nerq.ai/v1/preflight?target=deepwiki-mcp
ما هي البدائل الأكثر أمانًا لـ Deepwiki Mcp؟
في فئة البنية التحتية، البدائل الأعلى تقييمًا تشمل langflow-ai/langflow (65/100), langgenius/dify (64/100), open-webui/open-webui (60/100). deepwiki-mcp scores 72.5/100.
كم مرة يتم تحديث درجة أمان Deepwiki Mcp؟
Nerq continuously monitors Deepwiki Mcp and updates its trust score as new data becomes available. Current: 72.5/100 (B), last موثق 2026-07-17. API: GET nerq.ai/v1/preflight?target=deepwiki-mcp
هل يمكنني استخدام Deepwiki Mcp في بيئة منظمة؟
Deepwiki Mcp يستوفي عتبة التحقق من Nerq (70+). آمن للاستخدام.
API: /v1/preflight Trust Badge واجهة برمجة التطبيقات Docs

انظر أيضاً

إخلاء المسؤولية: درجات ثقة Nerq هي تقييمات آلية مبنية على إشارات متاحة للعموم. وهي ليست توصيات أو ضمانات. قم دائمًا بإجراء العناية الواجبة الخاصة بك.

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