Is Memory Mcp Safe?
Exercise caution with Memory Mcp. Memory Mcp is a software tool with a Nerq Trust Score of 47.8/100 (D), based on 3 independent data dimensions. It is below the recommended threshold of 70. Maintenance: 0/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-24. Machine-readable data (JSON).
Is Memory Mcp safe?
NO — USE WITH CAUTION — Memory Mcp has a Nerq Trust Score of 47.8/100 (D). It has below-average trust signals with significant gaps in security, maintenance, or documentation. Not recommended for production use without thorough manual review and additional security measures.
Trust Score Breakdown
Key Findings
Details
| Author | https://github.com/chenxiaofie/memory-mcp |
| Category | infrastructure |
| Stars | 85 |
| Source | https://github.com/yuvalsuede/memory-mcp |
Popular Alternatives in infrastructure
What Is Memory Mcp?
Memory Mcp is a software tool in the infrastructure category: Automatically extracts and organizes project memories from conversation transcripts, maintaining both quick-access CLAUDE.md files and comprehensive .memory/state.json stores for persistent project knowledge across sessions.. It has 85 GitHub stars. Nerq Trust Score: 48/100 (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 Mcp's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Memory Mcp performs in each:
- Maintenance (0/100): Memory 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 documentation, usage examples, and contribution guidelines.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 47.8/100 (D) reflects the weighted combination of these signals. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.
Who Should Use Memory Mcp?
Memory 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: We recommend caution with Memory Mcp. 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 Mcp'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 known vulnerabilities in Memory Mcp's dependency tree. - Review permissions — Understand what access Memory Mcp requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Memory 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=Memory MCP - Review the license — Confirm that Memory 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 security concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Memory Mcp
When evaluating whether Memory Mcp is safe, consider these category-specific risks:
Understand how Memory Mcp processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Memory Mcp's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Memory Mcp. Security patches and bug fixes are only effective if you're running the latest version.
If Memory 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 Memory 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 Memory Mcp in violation of its license can expose your organization to legal liability.
Best Practices for Using Memory Mcp Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Memory Mcp while minimizing risk:
Periodically review how Memory Mcp is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Memory Mcp and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Memory Mcp only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Memory Mcp'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 Mcp is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Memory Mcp?
Even promising tools aren't right for every situation. Consider avoiding Memory Mcp 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 Mcp's trust score of 47.8/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Memory 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. Memory Mcp's score of 47.8/100 is below the category average of 62/100.
This suggests that Memory Mcp trails behind many comparable infrastructure 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.
Trust Score History
Nerq continuously monitors Memory 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 maintenance patterns change, Memory 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 Memory Mcp's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Memory 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 Memory Mcp are strengthening or weakening over time.
Memory Mcp vs Alternatives
In the infrastructure category, Memory Mcp scores 47.8/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Memory Mcp vs n8n — Trust Score: 78.5/100
- Memory Mcp vs langflow — Trust Score: 87.6/100
- Memory Mcp vs dify — Trust Score: 79.1/100
Key Takeaways
- Memory Mcp has a Trust Score of 47.8/100 (D) and is not yet Nerq Verified.
- Memory Mcp has significant trust gaps. Consider higher-rated alternatives unless specific requirements mandate its use.
- Among infrastructure tools, Memory Mcp 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.
Frequently Asked Questions
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Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.