What is AI Sessions?
AI Sessions is a AI tool that Provides unified access to local AI assistant CLI session histories from Claude Code, Gemini CLI, and OpenAI Codex with tools for listing, browsing, searching, and retrieving session transcripts acros. It has a Nerq Trust Score of 43/100 (E). 22 GitHub stars. Published by https://github.com/yoavf/ai-sessions-mcp. Last analyzed September 2026.
Why This Score
- ⚠️ Security: 0/100 — Some security concerns
- ⚠️ Maintenance: 0/100 — Maintenance activity is low
- ⚠️ Community: 22 stars, 0 downloads — Growing community
- ⚠️ Transparency: License: Not specified — No license specified
Trust & Safety Overview
What AI Sessions Does
AI Sessions is a mcp_server in the AI tool category. Provides unified access to local AI assistant CLI session histories from Claude Code, Gemini CLI, and OpenAI Codex with tools for listing, browsing, searching, and retrieving session transcripts across different storage formats for finding past solutions and resuming interrupted coding sessions.. It is published by https://github.com/yoavf/ai-sessions-mcp and has no specified license. With 22 GitHub stars and 0 downloads, it has a small community of users and contributors.
Who Should Use AI Sessions
AI Sessions is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.
Details
| Author | https://github.com/yoavf/ai-sessions-mcp |
|---|---|
| Category | AI tool |
| License | Not specified |
| Type | mcp_server |
| Source | View on GitHub |
| Security Score | 0/100 |
| Activity Score | 0/100 |
How to Get Started
Check the trust score before installing:
curl nerq.ai/v1/preflight?target=ai-sessions
Setup guide · Full safety report · Production review · Is it safe?
Safer Alternatives
| Tool | Trust | Stars |
|---|---|---|
| MarkItDown | 42 | 92.8K |
| Filesystem | 50 | 89.4K |
| Time | 50 | 89.4K |
| Sequential Thinking | 50 | 89.4K |
| Fetch | 50 | 89.4K |
Frequently Asked Questions
Last updated September 2026. Trust scores based on automated analysis of public data.