Is Mcp Knowledge Graph Safe?
Mcp Knowledge Graph is a software tool with a Nerq Trust Score of 64.3/100 (C). It is below the recommended threshold of 70. Maintenance: 0/100. Popularity: 1/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-23. Machine-readable data (JSON).
Is Mcp Knowledge Graph safe?
CAUTION — Mcp Knowledge Graph has a Nerq Trust Score of 64.3/100 (C). It has moderate trust signals but shows some areas of concern that warrant attention. Suitable for development use — review security and maintenance signals before production deployment.
Trust Score Breakdown
Key Findings
Details
| Author | shaneholloman |
| Category | infrastructure |
| Stars | 795 |
| Source | https://github.com/shaneholloman/mcp-knowledge-graph |
| Protocols | mcp |
Regulatory Compliance
| EU AI Act Risk Class | Not assessed |
| Compliance Score | 80/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in infrastructure
Mcp Knowledge Graph Across Platforms
Same developer/company in other registries:
What Is Mcp Knowledge Graph?
Mcp Knowledge Graph is a software tool in the infrastructure category: MCP server enabling persistent memory for Claude through a local knowledge graph - fork focused on local development. It has 795 GitHub stars. Nerq Trust Score: 64/100 (C).
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 Mcp Knowledge Graph's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Mcp Knowledge Graph performs in each:
- Maintenance (0/100): Mcp Knowledge Graph 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.
- Compliance (80/100): Mcp Knowledge Graph is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (1/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 64.3/100 (C) 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 Mcp Knowledge Graph?
Mcp Knowledge Graph 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: Mcp Knowledge Graph is suitable for development and testing environments. Before production deployment, conduct a thorough review of its security posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Mcp 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 known vulnerabilities in Mcp Knowledge Graph's dependency tree. - Review permissions — Understand what access Mcp Knowledge Graph requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Mcp 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=mcp-knowledge-graph - Review the license — Confirm that Mcp 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 Mcp Knowledge Graph
When evaluating whether Mcp Knowledge Graph is safe, consider these category-specific risks:
Understand how Mcp 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 Mcp Knowledge Graph's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Mcp Knowledge Graph. Security patches and bug fixes are only effective if you're running the latest version.
If Mcp 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 Mcp 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 Mcp Knowledge Graph in violation of its license can expose your organization to legal liability.
Best Practices for Using Mcp Knowledge Graph Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Mcp Knowledge Graph while minimizing risk:
Periodically review how Mcp Knowledge Graph is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Mcp Knowledge Graph and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Mcp Knowledge Graph only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Mcp 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 Mcp Knowledge Graph is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Mcp Knowledge Graph?
Even promising tools aren't right for every situation. Consider avoiding Mcp 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 Mcp Knowledge Graph's trust score of 64.3/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Mcp Knowledge Graph 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. Mcp Knowledge Graph's score of 64.3/100 is above the category average of 62/100.
This positions Mcp Knowledge Graph favorably among infrastructure tools. While it outperforms the average, there is still room for improvement in certain trust dimensions.
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 Mcp Knowledge Graph 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, Mcp 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 Mcp Knowledge Graph's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=mcp-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 Mcp Knowledge Graph are strengthening or weakening over time.
Mcp Knowledge Graph vs Alternatives
In the infrastructure category, Mcp Knowledge Graph scores 64.3/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Mcp Knowledge Graph vs n8n — Trust Score: 78.5/100
- Mcp Knowledge Graph vs langflow — Trust Score: 87.6/100
- Mcp Knowledge Graph vs dify — Trust Score: 79.1/100
Key Takeaways
- Mcp Knowledge Graph has a Trust Score of 64.3/100 (C) and is not yet Nerq Verified.
- Mcp Knowledge Graph shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among infrastructure tools, Mcp Knowledge Graph scores above the category average of 62/100, demonstrating above-average reliability.
- 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.