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io.github.vnbochkarev-netizen/vibo-memory

Official

by vnbochkarev-netizen · Python

Memory for AI agents: persistent L1/L2/L3, web-search savings, thread memory.

Memory for AI agents: persistent L1/L2/L3 memory, reduced web-search needs (“web-search savings”), and thread memory. The server is documented as “ViBo — Memory for AI Agents + Living Document Archive,” focused on retaining agent context and archived documents.

🛠️ Key Features

  • Persistent L1/L2/L3 memory
  • Web-search savings
  • Thread memory

🚀 Use Cases

  • Supporting long-running agent conversations with thread memory
  • Preserving context across sessions via layered (L1/L2/L3) memory
  • Storing and revisiting documents through a “living document archive”

⚡ Developer Benefits

  • Enables semantic-search and vector-memory workflows (via provided topics)
  • Agent-skills orientation for building LLM assistants that retain context
  • Relevance to Claude integrations (as referenced by topics)

⚠️ Limitations

  • No tool count, API details, or supported interfaces are provided in the available data.

Topics

agentsaillmmemorysemantic-searchagent-skillsclaudecontext-compressionopenclawvector-memory