Persistent, verified memory for coding agents — so they stop re-explaining your codebase and never act on stale knowl...
Copy the install, test the workflow, then decide if it earns a permanent slot.
The signal is softer here. Treat it like a pattern source unless it solves a very specific gap.
Copy the install, test the workflow, then decide if it earns a permanent slot.
You can test this quickly and remove it cleanly if it misses.
GitHub health 75/100. no security policy. 7 open issues make this testable, but not something to trust blind.
AI Agent
Universal
Model
Multiple
Fastest way to find out if Kage belongs in your setup.
Copy the install command, run a real test, and back it out cleanly if it slows you down.
git clone https://github.com/kage-core/Kage && cd kage && cat README.mdRun this first. You will know quickly if the workflow earns a permanent slot.
rm -rf kageNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
./ └─ kage/ ← clones here
Persistent, verified memory for coding agents — so they stop re-explaining your codebase and never act on stale knowledge. Every memory is checked against your actual code; lives in your repo as plain files, shared via git. No account, no DB. Install: npx -y @kage-core/kage-graph-mcp install
Source: GitHub repository
Source check: July 18, 2026
Upstream commit: July 10, 2026
Repository state: Not marked archived
Honeystax upvotes are community interest signals, not star ratings. GitHub stars and repository health are source measurements; editorial risk and trial-cost notes are Honeystax analysis.