Is Bun Runtime Mcp Safe?
Bun Runtime Mcp — Nerq Trust Score 50.9/100 (D grade). Score based on 5 independent trust signals.
Bun Runtime Mcp is a software tool with a Nerq Trust Score of 50.9/100 (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 Bun Runtime Mcp safe?
Trust Score Breakdown — Bun Runtime Mcp has a Nerq Trust Score of 50.9/100 (D). Measured across 5 independent trust signals.
What is Bun Runtime Mcp's trust score?
Bun Runtime Mcp has a Nerq Trust Score of 50.9/100, 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 Bun Runtime Mcp?
Bun Runtime Mcp's strongest signal is compliance at 100/100. No known vulnerabilities have been detected.
What is Bun Runtime Mcp and who maintains it?
| Author | idyllic-labs |
| Category | Devops |
| Source | https://github.com/idyllic-labs/bun-runtime-mcp |
| Frameworks | anthropic |
| Protocols | mcp · rest · websocket |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in devops
What Is Bun Runtime Mcp?
Bun Runtime Mcp is a DevOps tool: Drop-in MCP server for inspecting and debugging running Bun processes.. Nerq Trust Score: 51/100 (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 Bun Runtime Mcp's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Bun Runtime Mcp performs in each:
- Security (0/100): Bun Runtime Mcp's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Bun Runtime Mcp 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): Bun Runtime Mcp 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 50.9/100 (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 Bun Runtime Mcp?
Bun Runtime Mcp is commonly evaluated by:
- Developers and teams working with devops tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Bun Runtime Mcp'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 Bun Runtime 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'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 Bun Runtime Mcp's dependency tree. - Review permissions — Understand what access Bun Runtime Mcp requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Bun Runtime 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=bun-runtime-mcp - Review the license — Confirm that Bun Runtime 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 Bun Runtime Mcp
When evaluating whether Bun Runtime Mcp is safe, consider these category-specific risks:
Understand how Bun Runtime Mcp processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Bun Runtime Mcp's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Bun Runtime Mcp. Security patches and bug fixes are only effective if you're running the latest version.
If Bun Runtime 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 Bun Runtime 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 Bun Runtime Mcp in violation of its license can expose your organization to legal liability.
Bun Runtime Mcp and the EU AI Act
Bun Runtime Mcp 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 Bun Runtime Mcp Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Bun Runtime Mcp while minimizing risk:
Periodically review how Bun Runtime Mcp is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Bun Runtime Mcp and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Bun Runtime Mcp only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Bun Runtime 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 Bun Runtime Mcp is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Bun Runtime Mcp
Nerq's signals are one input. In the following situations, evaluate Bun Runtime 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 Bun Runtime Mcp's measured trust score of 50.9/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Bun Runtime Mcp is suitable for any particular use.
How Bun Runtime Mcp Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among DevOps tools, the average Trust Score is 63/100. Bun Runtime Mcp's score of 50.9/100 is below the category average of 63/100.
This suggests that Bun Runtime Mcp trails behind many comparable DevOps 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 Bun Runtime 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, Bun Runtime 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 Bun Runtime Mcp's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=bun-runtime-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 Bun Runtime Mcp are strengthening or weakening over time.
Bun Runtime Mcp vs Alternatives
In the devops category, Bun Runtime Mcp scores 50.9/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Bun Runtime Mcp vs ansible — Trust Score: 74.9/100
- Bun Runtime Mcp vs Flowise — Trust Score: 67.5/100
- Bun Runtime Mcp vs learn-claude-code — Trust Score: 76.1/100
Key Takeaways
- Bun Runtime Mcp has a measured Nerq Trust Score of 50.9/100 (D) — a composite of independent signals, not a suitability judgment.
- Among DevOps tools, Bun Runtime Mcp scores below the category average of 63/100 (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 Bun Runtime Mcp Safe?
What is Bun Runtime Mcp's trust score?
What are safer alternatives to Bun Runtime Mcp?
How often is Bun Runtime Mcp's safety score updated?
Can I use Bun Runtime Mcp in a regulated environment?
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.