Memory Knowledge Graph安全吗?
Memory Knowledge Graph — Nerq 信任评分 46.1/100 (D级). 基于5个信任维度的分析,被评估为存在值得注意的安全问题。 最后更新:2026-03-31。
请对Memory Knowledge Graph保持警惕。 Memory Knowledge Graph is a software tool Nerq 信任评分为 46.1/100 (D). 低于推荐阈值 70。 Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-31. 机器可读数据(JSON).
Memory Knowledge Graph安全吗?
否——请谨慎使用 — Memory Knowledge Graph Nerq 信任评分为 46.1/100 (D). 信任信号低于平均水平,在安全性、维护或文档方面存在重大缺口. 未经彻底手动审查和额外安全措施,不建议用于生产环境.
Memory Knowledge Graph的信任评分是多少?
Memory Knowledge Graph Nerq 信任评分为 46.1/100, earning a D grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
Memory Knowledge Graph的主要安全发现是什么?
Memory Knowledge Graph's strongest signal is 整体信任度 at 46.1/100. No 已知漏洞 have been detected. It has not yet reached the Nerq Verified threshold of 70+.
Memory Knowledge Graph是什么,谁在维护它?
| 开发者 | https://github.com/okooo5km/memory-mcp-server |
| 类别 | uncategorized |
| 星标 | 103 |
| 来源 | https://github.com/okooo5km/memory-mcp-server |
What Is Memory Knowledge Graph?
Memory Knowledge Graph is a software tool in the uncategorized category: Provides a persistent knowledge graph system for maintaining structured memory across conversations, enabling creation, querying, and management of entities and relationships through specialized graph operation tools.. It has 103 GitHub stars. Nerq 信任评分: 46/100 (D).
Nerq independently analyzes every software tool, app, and extension across multiple trust signals including security vulnerabilities, maintenance activity, license compliance, and community adoption.
How Nerq Assesses Memory Knowledge Graph's Safety
Nerq evaluates every software tool across 13+ independent trust signals drawn from public sources including GitHub, NVD, OSV.dev, OpenSSF Scorecard, and package registries. These signals are grouped into five core dimensions: 安全性 (known CVEs, dependency vulnerabilities, security policies), 维护 (commit frequency, release cadence, issue response times), Documentation (README quality, API docs, examples), Compliance (license, regulatory alignment across 52 jurisdictions), and Community (stars, forks, downloads, ecosystem integrations).
Memory Knowledge Graph receives an overall 信任评分 of 46.1/100 (D), which Nerq considers low. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.
Nerq updates trust scores continuously as new data becomes available. To get the latest assessment, query the API: GET nerq.ai/v1/preflight?target=Memory Knowledge Graph
Each dimension is weighted according to its importance for the tool's category. For example, Security and Maintenance carry higher weight for tools that handle sensitive data or execute code, while Community and Documentation are weighted more heavily for developer-facing libraries and frameworks. This ensures that Memory Knowledge Graph's score reflects the risks most relevant to its actual usage patterns. The final score is a weighted average across all five dimensions, normalized to a 0-100 scale with letter grades from A (highest) to F (lowest).
Who Should Use Memory Knowledge Graph?
Memory Knowledge Graph is designed for:
- Developers and teams working with uncategorized tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: We recommend caution with Memory Knowledge Graph. The low trust score suggests potential risks in security, maintenance, or community support. Consider using a more established alternative for any production or sensitive workload.
How to Verify Memory Knowledge Graph's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any software tool:
- Check the source code — Review the repository security policy, open issues, and recent commits for signs of active maintenance.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for 已知漏洞 in Memory Knowledge Graph's dependency tree. - 评论 permissions — Understand what access Memory Knowledge Graph requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Memory Knowledge Graph 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=Memory Knowledge Graph - 查看 license — Confirm that Memory Knowledge Graph'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 security concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Memory Knowledge Graph
When evaluating whether Memory Knowledge Graph is safe, consider these category-specific risks:
Understand how Memory Knowledge Graph processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Memory Knowledge Graph's dependency tree for 已知漏洞. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Memory Knowledge Graph. Security patches and bug fixes are only effective if you're running the latest version.
If Memory Knowledge Graph 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 Memory Knowledge Graph's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Memory Knowledge Graph in violation of its license can expose your organization to legal liability.
Best Practices for Using Memory Knowledge Graph Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Memory Knowledge Graph while minimizing risk:
Periodically review how Memory Knowledge Graph is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Memory Knowledge Graph and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Memory Knowledge Graph only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Memory Knowledge Graph's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Memory Knowledge Graph is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Memory Knowledge Graph?
Even promising tools aren't right for every situation. Consider avoiding Memory Knowledge Graph in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional compliance review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Memory Knowledge Graph的信任评分为 46.1/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Memory Knowledge Graph Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among uncategorized tools, the average 信任评分 is 62/100. Memory Knowledge Graph's score of 46.1/100 is below the category average of 62/100.
This suggests that Memory Knowledge Graph trails behind many comparable uncategorized tools. Organizations with strict security requirements should evaluate whether higher-scoring alternatives better meet their needs.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderate 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.
信任评分 History
Nerq continuously monitors Memory Knowledge Graph and recalculates its 信任评分 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, Memory Knowledge Graph'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 Memory Knowledge Graph's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Memory Knowledge Graph&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 Memory Knowledge Graph are strengthening or weakening over time.
主要结论
- Memory Knowledge Graph has a 信任评分 of 46.1/100 (D) and is not yet Nerq Verified.
- Memory Knowledge Graph has significant trust gaps. Consider higher-rated alternatives unless specific requirements mandate its use.
- Among uncategorized tools, Memory Knowledge Graph scores below the category average of 62/100, suggesting room for improvement relative to peers.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
常见问题
Memory Knowledge Graph可以安全使用吗?
Memory Knowledge Graph's trust score是什么?
Memory Knowledge Graph有哪些更安全的替代品?
How often is Memory Knowledge Graph's safety score updated?
我可以在受监管环境中使用Memory Knowledge Graph吗?
Disclaimer: Nerq 信任评分是基于公开信号的自动评估。它们不构成建议或保证。请始终进行自己的验证。