Is Memory Mcp Safe?
Memory Mcp — Nerq Trust Score 47.8/100 (D grade). Score based on 3 independent trust signals.
Memory Mcp is a software tool with a Nerq Trust Score of 47.8/100 (D), based on 3 independent data dimensions. Maintenance: 0/100. 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 Memory Mcp safe?
Trust Score Breakdown — Memory Mcp has a Nerq Trust Score of 47.8/100 (D). Measured across 3 independent trust signals.
What is Memory Mcp's trust score?
Memory Mcp has a Nerq Trust Score of 47.8/100, earning a D grade. This score is based on 3 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Memory Mcp?
Memory Mcp's strongest signal is maintenance at 0/100. No known vulnerabilities have been detected.
What is Memory Mcp and who maintains it?
| 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) 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 Memory Mcp?
Memory Mcp 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: Memory Mcp's measured signals (maintenance 0/100, documentation 0/100, 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 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.
Situations That Warrant Independent Review of Memory Mcp
Nerq's signals are one input. In the following situations, evaluate Memory Mcp'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 Memory Mcp's measured trust score of 47.8/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Memory Mcp is suitable for any particular use.
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: 69.1/100
- Memory Mcp vs langflow — Trust Score: 81.0/100
- Memory Mcp vs dify — Trust Score: 69.7/100
Key Takeaways
- Memory Mcp has a measured Nerq Trust Score of 47.8/100 (D) — a composite of independent signals, not a suitability judgment.
- Among infrastructure tools, Memory Mcp scores below 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
Is Memory Mcp Safe?
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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.