Is Memvid Rag Safe?
Memvid Rag — Nerq Trust Score 56.6/100 (D grade). Score based on 5 independent trust signals.
Memvid Rag is a software tool with a Nerq Trust Score of 56.6/100 (D), based on 5 independent data dimensions. Security: 0/100. Maintenance: 1/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: n/a. Machine-readable data (JSON).
Is Memvid Rag safe?
Trust Score Breakdown — Memvid Rag has a Nerq Trust Score of 56.6/100 (D). Measured across 5 independent trust signals.
What is Memvid Rag's trust score?
Memvid Rag has a Nerq Trust Score of 56.6/100, earning a D grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Memvid Rag?
Memvid Rag's strongest signal is compliance at 100/100. No known vulnerabilities have been detected.
What is Memvid Rag and who maintains it?
| Author | fa-ina-tic |
| Category | Coding |
| Stars | 2 |
| Source | https://github.com/fa-ina-tic/memvid-rag |
| Frameworks | openai · anthropic |
| Protocols | rest |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in coding
What Is Memvid Rag?
Memvid Rag is a software tool in the coding category: Local, multimodal RAG agent for Claude Code.. It has 2 GitHub stars. Nerq Trust Score: 57/100 (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 Memvid Rag's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Memvid Rag performs in each:
- Security (0/100): Memvid Rag's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Memvid Rag 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 documentation, usage examples, and contribution guidelines.
- Compliance (100/100): Memvid Rag is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 56.6/100 (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 Memvid Rag?
Memvid Rag is commonly evaluated by:
- Developers and teams working with coding tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Memvid Rag's measured signals (security 0/100, maintenance 1/100, documentation 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 Memvid Rag'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's security policy, open issues, and recent commits for signs of active maintenance.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Memvid Rag's dependency tree. - Review permissions — Understand what access Memvid Rag requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Memvid Rag 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=memvid-rag - Review the license — Confirm that Memvid Rag'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 Memvid Rag
When evaluating whether Memvid Rag is safe, consider these category-specific risks:
Understand how Memvid Rag processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Memvid Rag's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Memvid Rag. Security patches and bug fixes are only effective if you're running the latest version.
If Memvid Rag 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 Memvid Rag's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Memvid Rag in violation of its license can expose your organization to legal liability.
Memvid Rag and the EU AI Act
Memvid Rag 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 compliance assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal compliance.
Best Practices for Using Memvid Rag Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Memvid Rag while minimizing risk:
Periodically review how Memvid Rag is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Memvid Rag and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Memvid Rag only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Memvid Rag's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Memvid Rag is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Memvid Rag
Nerq's signals are one input. In the following situations, evaluate Memvid Rag'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 Memvid Rag's measured trust score of 56.6/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Memvid Rag is suitable for any particular use.
How Memvid Rag Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among coding tools, the average Trust Score is 62/100. Memvid Rag's score of 56.6/100 is near the category average of 62/100.
This places Memvid Rag in line with the typical coding 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 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.
Trust Score History
Nerq continuously monitors Memvid Rag 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 maintenance patterns change, Memvid Rag'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 Memvid Rag's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=memvid-rag&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 Memvid Rag are strengthening or weakening over time.
Memvid Rag vs Alternatives
In the coding category, Memvid Rag scores 56.6/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Memvid Rag vs AutoGPT — Trust Score: 65.3/100
- Memvid Rag vs ollama — Trust Score: 64.4/100
- Memvid Rag vs langchain — Trust Score: 77.0/100
Key Takeaways
- Memvid Rag has a measured Nerq Trust Score of 56.6/100 (D) — a composite of independent signals, not a suitability judgment.
- Among coding tools, Memvid Rag scores near the category average of 62/100 (a positional measurement relative to peers).
- The individual signals — security, maintenance, documentation, compliance, community — are shown above. Weigh them against your own requirements.
- Query the current measured values via Nerq's Preflight API.
Frequently Asked Questions
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See Also
Disclaimer: Nerq trust scores are automated measurements based on publicly available signals. They are not endorsements, verdicts, or guarantees of suitability. Always evaluate the signals against your own requirements.