Is Paper Search Mcp Safe?
Paper Search Mcp — Nerq Trust Score 53.6/100 (D grade). Score based on 5 independent trust signals.
Paper Search Mcp is a software tool with a Nerq Trust Score of 53.6/100 (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 Paper Search Mcp safe?
Trust Score Breakdown — Paper Search Mcp has a Nerq Trust Score of 53.6/100 (D). Measured across 5 independent trust signals.
What is Paper Search Mcp's trust score?
Paper Search Mcp has a Nerq Trust Score of 53.6/100, 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 Paper Search Mcp?
Paper Search Mcp's strongest signal is compliance at 100/100. No known vulnerabilities have been detected.
What is Paper Search Mcp and who maintains it?
| Author | BlaineHeffron |
| Category | Research |
| Source | https://github.com/BlaineHeffron/paper-search-mcp |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 100/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in research
What Is Paper Search Mcp?
Paper Search Mcp is a software tool in the research category: MCP server for searching, indexing, and retrieving scientific papers.. Nerq Trust Score: 54/100 (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 Paper Search Mcp's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Paper Search Mcp performs in each:
- Security (0/100): Paper Search Mcp's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Paper Search Mcp 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 (100/100): Paper Search 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 53.6/100 (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 Paper Search Mcp?
Paper Search Mcp is commonly evaluated by:
- Developers and teams working with research tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
How to read the signals: Paper Search Mcp's measured signals (security 0/100, maintenance 1/100, documentation 0/100, 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 Paper Search 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 Paper Search Mcp's dependency tree. - Review permissions — Understand what access Paper Search Mcp requires. Software tools should follow the principle of least privilege.
- Test in isolation — Run Paper Search 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=paper-search-mcp - Review the license — Confirm that Paper Search 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 Paper Search Mcp
When evaluating whether Paper Search Mcp is safe, consider these category-specific risks:
Understand how Paper Search Mcp processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Paper Search Mcp's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Paper Search Mcp. Security patches and bug fixes are only effective if you're running the latest version.
If Paper Search 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 Paper Search 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 Paper Search Mcp in violation of its license can expose your organization to legal liability.
Paper Search Mcp and the EU AI Act
Paper Search 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 Paper Search Mcp Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Paper Search Mcp while minimizing risk:
Periodically review how Paper Search Mcp is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Paper Search Mcp and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Paper Search Mcp only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Paper Search 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 Paper Search Mcp is used within your organization, including data handling guidelines and acceptable use cases.
Situations That Warrant Independent Review of Paper Search Mcp
Nerq's signals are one input. In the following situations, evaluate Paper Search 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 Paper Search Mcp's measured trust score of 53.6/100 and its individual signals against your organization's own criteria. Nerq does not assert whether Paper Search Mcp is suitable for any particular use.
How Paper Search Mcp 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. Paper Search Mcp's score of 53.6/100 is near the category average of 62/100.
This places Paper Search Mcp in line with the typical research 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 Paper Search 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, Paper Search 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 Paper Search Mcp's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=paper-search-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 Paper Search Mcp are strengthening or weakening over time.
Paper Search Mcp vs Alternatives
In the research category, Paper Search Mcp scores 53.6/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Paper Search Mcp vs gpt_academic — Trust Score: 60.9/100
- Paper Search Mcp vs LlamaFactory — Trust Score: 79.7/100
- Paper Search Mcp vs unsloth — Trust Score: 77.2/100
Key Takeaways
- Paper Search Mcp has a measured Nerq Trust Score of 53.6/100 (D) — a composite of independent signals, not a suitability judgment.
- Among research tools, Paper Search Mcp 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
Is Paper Search Mcp Safe?
What is Paper Search Mcp's trust score?
What are safer alternatives to Paper Search Mcp?
How often is Paper Search Mcp's safety score updated?
Can I use Paper Search 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.