{"repo":"Edlineas/aivectormemory","free":true,"listed":false,"github":"https://github.com/Edlineas/aivectormemory","clone":"git clone https://github.com/Edlineas/aivectormemory.git","description":"aivectormemory 是一款基于 Model Context Protocol (MCP) 开发的OpenClaw、OpenCode、ClaudeCodeAI记忆管理工具。它专门为 Claude、OpenCode、Cursor 和 主流IDE 编程工具设计，通过向量数据库技术解决 AI 在不同对话会话中「健忘」的问题。aivectormemory: A lightweight MCP Server enabling persistent, cross-session memory for AI-powered IDEs via vector search.","language":"Python","stars":91,"topics":["claudecode","claudecode-hooks","openclaw","openclaw-plugin","opencode","opencode-plugin","opencode-skills","cursor","kiro","vscode-extension"],"license":"Apache-2.0","category":"mcp-servers","readme_excerpt":"🌐 简体中文 繁體中文 English Español Deutsch Français 日本語 AIVectorMemory Give your AI coding assistant a memory — Cross-session persistent memory MCP Server --- Still using CLAUDE.md / MEMORY.md as memory? This Markdown-file memory approach has fatal flaws: the file keeps growing, injecting everything into every session and burning massive tokens; content only supports keyword matching — search \"database timeout\" and you won't find \"MySQL connection pool pitfall\"; sharing one file across projects causes cross-contamination; there's no task tracking, so dev progress lives entirely in your head; not to mention the 200-line truncation, manual maintenance, and inability to deduplicate or merge. AIVectorMemory is a fundamentally different approach. Local vector database storage with semantic search for precise recall (matches even when wording differs), on-demand retrieval that loads only relevant memories (token usage drops 50%+), automatic multi-project isolation with zero interference, and built-in issue tracking + task management that lets AI fully automate your dev workflow. All data is permanently stored on your machine — zero cloud dependency, never lost when switching sessions or IDEs. ✨ Core Features Feature Description --------- ------------- 🧠 Cross-Session Memory Your AI finally remembers your project — pitfalls, decisions, conventions all persist across sessions 🔍 Hybrid Smart Search FTS5 full-text + vector semantic dual-path search, RRF fusion ranking + composite scoring (","default_branch":null,"files":null,"tree":[],"storefront":"/r/Edlineas","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Edlineas/aivectormemory/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}