Multi-Agent-Research-Team vs gpt_academic — Trust Score Comparison
Side-by-side trust comparison of Multi-Agent-Research-Team and gpt_academic. Scores based on security, compliance, maintenance, popularity, and ecosystem signals.
Detailed Metric Comparison
| Metric | Multi-Agent-Research-Team | gpt_academic |
|---|---|---|
| Trust Score | 0.0/100 | 0.0/100 |
| Grade | D | C |
| Stars | 0 | 70,114 |
| Category | uncategorized | research |
| Security | 0 | 0 |
| Compliance | 100 | 79 |
| Maintenance | 0 | 1 |
| Documentation | 0 | 0 |
| EU AI Act Risk | N/A | minimal |
| Verified | No | No |
Verdict
Multi-Agent-Research-Team (0.0) and gpt_academic (0.0) have nearly identical trust scores. Both are solid choices. The decision should come down to your specific use case, team preferences, and integration requirements rather than trust differences.
Detailed Analysis
Security
Multi-Agent-Research-Team leads on security with a score of 0/100 compared to gpt_academic's 0/100. This score reflects dependency vulnerability analysis, known CVE exposure, and security best practices. A higher security score means fewer known vulnerabilities and better security hygiene in the codebase.
Maintenance & Activity
gpt_academic demonstrates stronger maintenance activity (1/100 vs 0/100). This metric captures commit frequency, issue response times, and release cadence. Actively maintained tools receive faster security patches and are less likely to accumulate technical debt.
Documentation
Multi-Agent-Research-Team has better documentation (0/100 vs 0/100). Good documentation reduces onboarding time and helps teams adopt the tool safely. This score evaluates README completeness, API documentation, code examples, and tutorial availability.
Community & Adoption
Multi-Agent-Research-Team has 0 GitHub stars while gpt_academic has 70,114. gpt_academic has significantly broader community adoption, which typically means more Stack Overflow answers, more third-party tutorials, and faster ecosystem development.
When to Choose Each Tool
Choose Multi-Agent-Research-Team if you need:
- Consider if it better fits your specific use case
Choose gpt_academic if you need:
- More actively maintained with faster release cadence
- Larger community (70,114 vs 0 stars)
Switching from Multi-Agent-Research-Team to gpt_academic (or vice versa)
When migrating between Multi-Agent-Research-Team and gpt_academic, consider these factors:
- API Compatibility: Multi-Agent-Research-Team (uncategorized) and gpt_academic (research) serve different categories, so migration may require significant refactoring.
- Security Review: Run a security audit after migration. Check the Multi-Agent-Research-Team safety report and gpt_academic safety report for known issues.
- Testing: Ensure your test suite covers all integration points before switching in production.
- Community Support: Multi-Agent-Research-Team has 0 stars and gpt_academic has 70,114. Larger communities typically mean better Stack Overflow answers and migration guides.
Related Pages
Frequently Asked Questions
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Last updated: 2026-09-23 | Data refreshed weekly
Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.