What is ChaseAI?
62/100
Trust Score (C)
⚠️ Use Caution
ChaseAI is a devops that ChaseAI is a local tray-based orchestrator for AI agents.. It has a Nerq Trust Score of 62/100 (C). 0 GitHub stars. Published by Mitriyweb. Last analyzed September 2026.
Why This Score
- ⚠️ Security: 0/100 — Some security concerns
- ⚠️ Maintenance: 1/100 — Maintenance activity is low
- ⚠️ Community: 0 stars, 0 downloads — Growing community
- ✅ Transparency: License: MIT — Clear licensing
Trust & Safety Overview
62
TRUST SCORE
C
GRADE
0
STARS
0
DOWNLOADS
What ChaseAI Does
ChaseAI is a agent in the devops category. ChaseAI is a local tray-based orchestrator for AI agents.. It is published by Mitriyweb and is open source. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.
Who Should Use ChaseAI
ChaseAI is suitable for evaluation and non-critical use. Review the trust score breakdown before using in production.
Details
| Author | Mitriyweb |
|---|---|
| Category | devops |
| License | MIT |
| Type | agent |
| Source | View on GitHub |
| Security Score | 0/100 |
| Activity Score | 1/100 |
How to Get Started
Check the trust score before installing:
curl nerq.ai/v1/preflight?target=chaseai
Setup guide · Full safety report · Production review · Is it safe?
Safer Alternatives
| Tool | Trust | Stars |
|---|---|---|
| ansible | 75 | 68.1K |
| Flowise | 68 | 49.6K |
| learn-claude-code | 76 | 42.5K |
| continue | 75 | 31.6K |
| agents | 79 | 29.1K |
Frequently Asked Questions
What is ChaseAI used for?
ChaseAI is a devops tool. ChaseAI is a local tray-based orchestrator for AI agents..
Is ChaseAI free?
License: MIT. ChaseAI has 0 GitHub stars.
Is ChaseAI safe?
ChaseAI has a Nerq Trust Score of 62/100 (C). Use with caution.
What are alternatives to ChaseAI?
Top alternatives: ansible, Flowise, learn-claude-code. See full comparison.
Safety Report Is It Safe?
Alternatives Prediction
Trending Leaderboard
Discover MCP Servers
Packages Models
Stats API
Last updated September 2026. Trust scores based on automated analysis of public data.