Apakah Mcpjungle Aman?
Mcpjungle — Nerq Trust Score 52.4/100 (Nilai D). Skor berdasarkan 3 independent trust signals.
Mcpjungle adalah software tool dengan Skor Kepercayaan Nerq sebesar 52.4/100 (D), based on 3 dimensi data independen. Pemeliharaan: 0/100. Popularitas: 1/100. 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 Mcpjungle Aman?
Rincian Skor Kepercayaan — Mcpjungle has a Nerq Trust Score of 52.4/100 (D). Measured across 3 independent trust signals.
Berapa skor kepercayaan Mcpjungle?
Mcpjungle memiliki Skor Kepercayaan Nerq 52.4/100 dengan nilai D. Skor ini didasarkan pada 3 dimensi yang diukur secara independen.
Apa temuan keamanan utama untuk Mcpjungle?
Sinyal terkuat Mcpjungle adalah popularitas pada 1/100. Tidak ada kerentanan yang diketahui terdeteksi.
Apa itu Mcpjungle dan siapa yang mengelolanya?
| Pembuat | https://github.com/mcpjungle/mcpjungle |
| Kategori | Infrastructure |
| Bintang | 893 |
| Sumber | https://github.com/mcpjungle/mcpjungle |
Alternatif Populer di infrastructure
What Is Mcpjungle?
Mcpjungle is a software tool in the infrastructure category: Self-hosted MCP tool registry and proxy server that enables centralized discovery, management, and secure access to multiple MCP servers through a unified gateway with authentication, access control, and audit trails.. It has 893 GitHub stars. Nerq Trust Score: 52/100 (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 Mcpjungle's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensi. Here is how Mcpjungle performs in each:
- Pemeliharaan (0/100): Mcpjungle 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 dokumentasi, usage examples, and contribution guidelines.
- Community (1/100): Community adoption is limited. Berdasarkan GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 52.4/100 (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 Mcpjungle?
Mcpjungle 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: Mcpjungle's measured signals (pemeliharaan 0/100, dokumentasi 0/100, community 1/100) 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 Mcpjungle's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Tinjau repository keamanan policy, open issues, and recent commits for signs of active pemeliharaan.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Mcpjungle's dependency tree. - Ulasan permissions — Understand what access Mcpjungle requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Mcpjungle 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=MCPJungle - Tinjau license — Confirm that Mcpjungle'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 keamanan concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Mcpjungle
When evaluating whether Mcpjungle is safe, consider these category-specific risks:
Understand how Mcpjungle processes, stores, and transmits your data. Tinjau tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Mcpjungle's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher keamanan risk.
Regularly check for updates to Mcpjungle. Keamanan patches and bug fixes are only effective if you're running the latest version.
If Mcpjungle 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 Mcpjungle's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Mcpjungle in violation of its license can expose your organization to legal liability.
Best Practices for Using Mcpjungle Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Mcpjungle while minimizing risk:
Periodically review how Mcpjungle is used in your workflow. Check for unexpected behavior, permissions drift, and kepatuhan with your keamanan policies.
Ensure Mcpjungle and all its dependencies are running the latest stable versions to benefit from keamanan patches.
Grant Mcpjungle only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Mcpjungle's keamanan advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Mcpjungle is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Mcpjungle
Nerq's signals are one input. In the following situations, evaluate Mcpjungle'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 Mcpjungle's measured trust score of 52.4/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Mcpjungle is suitable for any particular use.
How Mcpjungle 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. Mcpjungle's score of 52.4/100 is near the category average of 62/100.
This places Mcpjungle 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 Mcpjungle 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, Mcpjungle'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 Mcpjungle's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=MCPJungle&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 Mcpjungle are strengthening or weakening over time.
Mcpjungle vs Alternatif
In the infrastructure category, Mcpjungle scores 52.4/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Mcpjungle vs n8n — Trust Score: 69.1/100
- Mcpjungle vs langflow — Trust Score: 77.0/100
- Mcpjungle vs dify — Trust Score: 69.7/100
Kesimpulan Utama
- Mcpjungle has a measured Nerq Trust Score of 52.4/100 (D) — a composite of independent signals, not a suitability judgment.
- Among infrastructure tools, Mcpjungle scores near the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — keamanan, pemeliharaan, dokumentasi, kepatuhan, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Pertanyaan yang Sering Diajukan
Apakah Mcpjungle Aman?
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