Is Pubmed Search Safe?
Pubmed Search — Nerq Trust Score 44.7/100 (E grade). Based on analysis of 3 trust dimensions, it is has notable safety concerns. Last updated: 2026-04-24.
Exercise caution with Pubmed Search. Pubmed Search is a software tool with a Nerq Trust Score of 44.7/100 (E), based on 3 independent data dimensions. Below the recommended threshold of 70. Maintenance: 0/100. Popularity: 0/100. Data sourced from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-04-24. Machine-readable data (JSON).
Is Pubmed Search safe?
NO — USE WITH CAUTION — Pubmed Search has a Nerq Trust Score of 44.7/100 (E). It has below-average trust signals with significant gaps in security, maintenance, or documentation. Not recommended for production use without thorough manual review and additional security measures.
What is Pubmed Search's trust score?
Pubmed Search has a Nerq Trust Score of 44.7/100, earning a E grade. This score is based on 3 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Pubmed Search?
Pubmed Search's strongest signal is maintenance at 0/100. No known vulnerabilities have been detected. It has not yet reached the Nerq Verified threshold of 70+.
What is Pubmed Search and who maintains it?
| Author | https://github.com/gradusnikov/pubmed-search-mcp-server |
| Category | Research |
| Stars | 47 |
| Source | https://github.com/wavelovey/pubmed_search |
Popular Alternatives in research
What Is Pubmed Search?
Pubmed Search is a software tool in the research category: Integrates with PubMed for natural language querying and analysis of biomedical literature.. It has 47 GitHub stars. Nerq Trust Score: 45/100 (E).
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 Pubmed Search's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Pubmed Search performs in each:
- Maintenance (0/100): Pubmed Search 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 44.7/100 (E) 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 Pubmed Search?
Pubmed Search is designed for:
- Developers and teams working with research tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: We recommend caution with Pubmed Search. The low trust score suggests potential risks in security, maintenance, or community support. Consider using a more established alternative for any production or sensitive workload.
How to Verify Pubmed Search'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 Pubmed Search's dependency tree. - Review permissions — Understand what access Pubmed Search requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Pubmed Search 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=PubMed Search - Review the license — Confirm that Pubmed Search'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 Pubmed Search
When evaluating whether Pubmed Search is safe, consider these category-specific risks:
Understand how Pubmed Search processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Pubmed Search's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Pubmed Search. Security patches and bug fixes are only effective if you're running the latest version.
If Pubmed Search 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 Pubmed Search's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Pubmed Search in violation of its license can expose your organization to legal liability.
Best Practices for Using Pubmed Search Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Pubmed Search while minimizing risk:
Periodically review how Pubmed Search is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Pubmed Search and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Pubmed Search only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Pubmed Search's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Pubmed Search is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Pubmed Search?
Even promising tools aren't right for every situation. Consider avoiding Pubmed Search 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 Pubmed Search's trust score of 44.7/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Pubmed Search Compares to Industry Standards
Nerq indexes over 6 million software tools, apps, and packages across dozens of categories. Among research tools, the average Trust Score is 62/100. Pubmed Search's score of 44.7/100 is below the category average of 62/100.
This suggests that Pubmed Search trails behind many comparable research 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 Pubmed Search 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, Pubmed Search'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 Pubmed Search's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=PubMed Search&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 Pubmed Search are strengthening or weakening over time.
Pubmed Search vs Alternatives
In the research category, Pubmed Search scores 44.7/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Pubmed Search vs gpt_academic — Trust Score: 71.3/100
- Pubmed Search vs LlamaFactory — Trust Score: 65.5/100
- Pubmed Search vs unsloth — Trust Score: 66.7/100
Key Takeaways
- Pubmed Search has a Trust Score of 44.7/100 (E) and is not yet Nerq Verified.
- Pubmed Search has significant trust gaps. Consider higher-rated alternatives unless specific requirements mandate its use.
- Among research tools, Pubmed Search scores below the category average of 62/100, suggesting room for improvement relative to peers.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Maintenance | 0/100 |
| Popularity | 0/100 |
Based on 2 dimensions. Data from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Pubmed Search collect?
Privacy assessment for Pubmed Search is not yet available. See our methodology for how Nerq measures privacy, or the public privacy review for any community-contributed notes.
Is Pubmed Search secure?
Security score: under assessment. Review security practices and consider alternatives with higher security scores for sensitive use cases.
Nerq monitors this entity against NVD, OSV.dev, and registry-specific vulnerability databases for ongoing security assessment.
Full analysis: Pubmed Search Security Report
How we calculated this score
Pubmed Search's trust score of 44.7/100 (E) is computed from multiple public sources including package registries, GitHub, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 2 independent dimensions: maintenance (0/100), popularity (0/100). Each dimension is weighted equally to produce the composite trust score.
Nerq analyzes over 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.
This page was last reviewed on April 24, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
Frequently Asked Questions
Is Pubmed Search Safe?
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Can I use Pubmed Search in a regulated environment?
See Also
Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.