Is Screaming Frog Mcp Safe? — Trust Score: 45.0/100
According to Nerq's independent analysis of screaming-frog-mcp, this infrastructure has a trust score of 45.0 out of 100, earning a D grade. With 1 stars on mcp, it is below the recommended threshold of 70. Security score: 0/100. Data sourced from 13+ independent signals including GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-18. Machine-readable data (JSON).
Is Screaming Frog Mcp safe?
NO — USE WITH CAUTION — Screaming Frog Mcp has a Nerq Trust Score of 45.0/100 (D). 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.
Trust Assessment
Caution — screaming-frog-mcp has below-average trust signals. There may be concerns around maintenance frequency, security practices, or ecosystem adoption. Proceed with care and conduct additional due diligence.
Trust Signal Breakdown
Details
| Author | bzsasson |
| Category | infrastructure |
| Stars | 1 |
| Source | https://github.com/bzsasson/screaming-frog-mcp |
| Protocols | mcp |
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What Is Screaming Frog Mcp?
Screaming Frog Mcp is a AI tool in the infrastructure category. MCP server for Screaming Frog SEO Spider – crawl sites, export data, and manage crawl storage via Claude or any MCP-compatible client
As of March 2026, Screaming Frog Mcp is available on mcp, making it an emerging tool in the AI ecosystem. But popularity alone does not equal safety — which is why Nerq independently analyzes every tool across 13+ trust signals.
How Nerq Assesses Screaming Frog Mcp's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Screaming Frog Mcp performs in each:
- Security (0/100): Screaming Frog Mcp's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (0/100): Screaming Frog 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.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 45.0/100 (D) 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 Screaming Frog Mcp?
Screaming Frog Mcp is designed for:
- Developers and teams working with infrastructure tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: We recommend caution with Screaming Frog Mcp. 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 Screaming Frog Mcp's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any AI 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 Screaming Frog Mcp's dependency tree. - Review permissions — Understand what access Screaming Frog Mcp requires. AI tools should follow the principle of least privilege.
- Test in isolation — Run Screaming Frog 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=screaming-frog-mcp - Review the license — Confirm that Screaming Frog 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 Screaming Frog Mcp
When evaluating whether Screaming Frog Mcp is safe, consider these category-specific risks:
Understand how Screaming Frog Mcp processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Screaming Frog Mcp's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Screaming Frog Mcp. Security patches and bug fixes are only effective if you're running the latest version.
If Screaming Frog 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 Screaming Frog 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 Screaming Frog Mcp in violation of its license can expose your organization to legal liability.
Best Practices for Using Screaming Frog Mcp Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Screaming Frog Mcp while minimizing risk:
Periodically review how Screaming Frog Mcp is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Screaming Frog Mcp and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Screaming Frog Mcp only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Screaming Frog 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 Screaming Frog Mcp is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Screaming Frog Mcp?
Even promising tools aren't right for every situation. Consider avoiding Screaming Frog Mcp 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 Screaming Frog Mcp's trust score of 45.0/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Screaming Frog Mcp Compares to Industry Standards
Nerq indexes over 204,000 AI agents and tools across dozens of categories. Among infrastructure tools, the average Trust Score is 62/100. Screaming Frog Mcp's score of 45.0/100 is below the category average of 62/100.
This suggests that Screaming Frog Mcp trails behind many comparable infrastructure 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 Screaming Frog 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, Screaming Frog 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 Screaming Frog Mcp's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=screaming-frog-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 Screaming Frog Mcp are strengthening or weakening over time.
Screaming Frog Mcp vs Alternatives
In the infrastructure category, Screaming Frog Mcp scores 45.0/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Screaming Frog Mcp vs n8n — Trust Score: 79.7/100
- Screaming Frog Mcp vs langflow — Trust Score: 87.6/100
- Screaming Frog Mcp vs dify — Trust Score: 80.3/100
Key Takeaways
- Screaming Frog Mcp has a Trust Score of 45.0/100 (D) and is not yet Nerq Verified.
- Screaming Frog Mcp has significant trust gaps. Consider higher-rated alternatives unless specific requirements mandate its use.
- Among infrastructure tools, Screaming Frog Mcp 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.
Frequently Asked Questions
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Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.