Context engineering for AI agents. ~80% fewer tokens. Fix tool overload. Skills and memory with in-process BM25 and s...
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 unknown. no security policy. 0 open issues make this testable, but not something to trust blind.
AI Agent
Universal
Model
Claude
Fastest way to find out if ratel belongs in your setup.
Copy the install command, run a real test, and back it out cleanly if it slows you down.
claude mcp add ratel -- npx ratelRun this first. You will know quickly if the workflow earns a permanent slot.
claude mcp remove ratelNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude.json └─ mcp_servers/ └─ ratel ← registers here
Context engineering for AI agents. ~80% fewer tokens. Fix tool overload. Skills and memory with in-process BM25 and semantic retrieval. No vector DB.
Source: GitHub repository
Source check: No source check recorded
Repository state: Not marked archived
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