Is Codex Mcp Rs Safe?
Codex Mcp Rs — Nerq Trust Score 66.4/100 (C grade). Score based on 5 independent trust signals.
Codex Mcp Rs is a software tool with a Nerq Trust Score of 66.4/100 (C), 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 Codex Mcp Rs safe?
Trust Score Breakdown — Codex Mcp Rs has a Nerq Trust Score of 66.4/100 (C). Measured across 5 independent trust signals.
What is Codex Mcp Rs's trust score?
Codex Mcp Rs has a Nerq Trust Score of 66.4/100, earning a C grade. This score is based on 5 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Codex Mcp Rs?
Codex Mcp Rs's strongest signal is compliance at 87/100. No known vulnerabilities have been detected.
What is Codex Mcp Rs and who maintains it?
| Author | missdeer |
| Category | Coding |
| Stars | 15 |
| Source | https://github.com/missdeer/codex-mcp-rs |
| Frameworks | anthropic |
| Protocols | mcp · rest |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 87/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in coding
Codex Mcp Rs Across Platforms
Same developer/company in other registries:
What Is Codex Mcp Rs?
Codex Mcp Rs is a software tool in the coding category: A Rust-based MCP server integrating AI coding assistants with Codex.. It has 15 GitHub stars. Nerq Trust Score: 66/100 (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 Codex Mcp Rs's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Codex Mcp Rs performs in each:
- Security (0/100): Codex Mcp Rs's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Codex Mcp Rs 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): Codex Mcp Rs 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 66.4/100 (C) 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 Codex Mcp Rs?
Codex Mcp Rs 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: Codex Mcp Rs'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 Codex Mcp Rs'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 Codex Mcp Rs's dependency tree. - Review permissions — Understand what access Codex Mcp Rs requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Codex Mcp Rs 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=codex-mcp-rs - Review the license — Confirm that Codex Mcp Rs'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 Codex Mcp Rs
When evaluating whether Codex Mcp Rs is safe, consider these category-specific risks:
Understand how Codex Mcp Rs processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Codex Mcp Rs's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Codex Mcp Rs. Security patches and bug fixes are only effective if you're running the latest version.
If Codex Mcp Rs 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 Codex Mcp Rs's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Codex Mcp Rs in violation of its license can expose your organization to legal liability.
Codex Mcp Rs and the EU AI Act
Codex Mcp Rs 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 Codex Mcp Rs Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Codex Mcp Rs while minimizing risk:
Periodically review how Codex Mcp Rs is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Codex Mcp Rs and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Codex Mcp Rs only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Codex Mcp Rs's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Codex Mcp Rs is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Codex Mcp Rs
Nerq's signals are one input. In the following situations, evaluate Codex Mcp Rs'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 Codex Mcp Rs's measured trust score of 66.4/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Codex Mcp Rs is suitable for any particular use.
How Codex Mcp Rs 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. Codex Mcp Rs's score of 66.4/100 is above the category average of 62/100.
This positions Codex Mcp Rs favorably among coding 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 Codex Mcp Rs 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, Codex Mcp Rs'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 Codex Mcp Rs's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=codex-mcp-rs&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 Codex Mcp Rs are strengthening or weakening over time.
Codex Mcp Rs vs Alternatives
In the coding category, Codex Mcp Rs scores 66.4/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Codex Mcp Rs vs AutoGPT — Trust Score: 65.3/100
- Codex Mcp Rs vs ollama — Trust Score: 64.4/100
- Codex Mcp Rs vs langchain — Trust Score: 77.0/100
Key Takeaways
- Codex Mcp Rs has a measured Nerq Trust Score of 66.4/100 (C) — a composite of independent signals, not a suitability judgment.
- Among coding tools, Codex Mcp Rs scores above 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.