🦞 ViBo MCP Server
Memory for AI agents — persistent memory (L1/L2/L3 encryption),
web-search savings and thread memory. Works with any MCP client:
Claude Desktop, Cursor, OpenClaw, Windsurf, Codex, and more.
Install
npm install -g @vibo-dev/@vibo-dev/vibo-mcp
Configuration
Add to your MCP client config (Claude Desktop example):
{
"mcpServers": {
"vibo": {
"command": "npx",
"args": ["-y", "@vibo-dev/@vibo-dev/vibo-mcp"],
"env": {
"VIBO_API_KEY": "YOUR_VIBO_KEY"
}
}
}
}
Get a key: https://wwwvibo.com — free 2-day trial, then $5/month.
Tools
memory_search | Find relevant facts (returns token savings) |
memory_add | Save a fact (dedup by exact match) |
memory_usage | Your real savings statistics |
thread_memory | Thread: add / compress / ask / context |
Example
Agent: "What does client Anna prefer?"
→ memory_search("Anna preferences")
→ • [L1] client-anna: Anna likes coffee without sugar, order #42
→ 💾 Saved 13,452 tokens (97.5%)
Honest numbers
- Memory: 97.5% fewer tokens on 118 facts (grows with memory, 50-150× on 10K+).
- Web search: 99.6% (measured 47,443 → 186 tokens).
- Threads: -72%.
- Secrets (L3) never reach the LLM — encrypted by design.
Links