Is Mcp Vibekanban Safe?
Mcp Vibekanban — Nerq Trust Score 52.4/100 (D grade). Score based on 5 independent trust signals.
Mcp Vibekanban is a software tool with a Nerq Trust Score of 52.4/100 (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 Mcp Vibekanban safe?
Trust Score Breakdown — Mcp Vibekanban has a Nerq Trust Score of 52.4/100 (D). Measured across 5 independent trust signals.
What is Mcp Vibekanban's trust score?
Mcp Vibekanban has a Nerq Trust Score of 52.4/100, 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 Mcp Vibekanban?
Mcp Vibekanban's strongest signal is compliance at 87/100. No known vulnerabilities have been detected.
What is Mcp Vibekanban and who maintains it?
| Author | yigitkonur |
| Category | Coding |
| Source | https://github.com/yigitkonur/mcp-vibekanban |
| Protocols | mcp |
Regulatory Compliance
| EU AI Act Risk Class | HIGH |
| Compliance Score | 87/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in coding
Mcp Vibekanban Across Platforms
Same developer/company in other registries:
What Is Mcp Vibekanban?
Mcp Vibekanban is a software tool in the coding category: Enhanced MCP server for Vibe Kanban project management, integrating AI for seamless task handling.. Nerq Trust Score: 52/100 (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 Mcp Vibekanban's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Mcp Vibekanban performs in each:
- Security (0/100): Mcp Vibekanban's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Mcp Vibekanban 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 (87/100): Mcp Vibekanban 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 52.4/100 (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 Mcp Vibekanban?
Mcp Vibekanban 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: Mcp Vibekanban'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 Mcp Vibekanban'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 Vibekanban's dependency tree. - Review permissions — Understand what access Mcp Vibekanban requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Mcp Vibekanban 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-vibekanban - Review the license — Confirm that Mcp Vibekanban'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 Vibekanban
When evaluating whether Mcp Vibekanban is safe, consider these category-specific risks:
Understand how Mcp Vibekanban processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Mcp Vibekanban's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Mcp Vibekanban. Security patches and bug fixes are only effective if you're running the latest version.
If Mcp Vibekanban 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 Vibekanban'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 Vibekanban in violation of its license can expose your organization to legal liability.
Mcp Vibekanban and the EU AI Act
Mcp Vibekanban is classified as High Risk under the EU AI Act. This imposes significant requirements including risk management systems, data governance, technical documentation, and human oversight.
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 Mcp Vibekanban Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Mcp Vibekanban while minimizing risk:
Periodically review how Mcp Vibekanban is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Mcp Vibekanban and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Mcp Vibekanban only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Mcp Vibekanban'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 Vibekanban is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Mcp Vibekanban
Nerq's signals are one input. In the following situations, evaluate Mcp Vibekanban'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 Mcp Vibekanban's measured trust score of 52.4/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Mcp Vibekanban is suitable for any particular use.
How Mcp Vibekanban 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. Mcp Vibekanban's score of 52.4/100 is near the category average of 62/100.
This places Mcp Vibekanban 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 Mcp Vibekanban 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 Vibekanban'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 Vibekanban's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=mcp-vibekanban&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 Vibekanban are strengthening or weakening over time.
Mcp Vibekanban vs Alternatives
In the coding category, Mcp Vibekanban scores 52.4/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Mcp Vibekanban vs AutoGPT — Trust Score: 65.3/100
- Mcp Vibekanban vs ollama — Trust Score: 64.4/100
- Mcp Vibekanban vs langchain — Trust Score: 77.0/100
Key Takeaways
- Mcp Vibekanban has a measured Nerq Trust Score of 52.4/100 (D) — a composite of independent signals, not a suitability judgment.
- Among coding tools, Mcp Vibekanban 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.