Long-term memory for AI coding agents. Works with Claude Code, ChatGPT, Cursor, Gemini CLI, VS Code Copilot, Windsurf, Claude Desktop, Codex CLI. Deploy once to Cloudflare Workers (free), use everywhere.
Long-term memory for AI coding agents — works with Claude Code, Cursor, Cursor, Cursor CLI, VS Code Cursor, Windsurf, Claude Desktop, Codex CLI. Deploy once to Cloudflare Workers (free tier), use everywhere.
讓你的 AI coding agent 擁有跨 session 的長期記憶。一次部署,所有 MCP 平台通用。
AI coding agent(Claude Code、Cursor、Cursor 等)每次對話都從零開始。你上次的架構決策、踩過的坑、偏好的工作方式 — 全部忘光。
這個 server 讓你的 AI agent 可以:
| 使用前 | 使用後 |
|---|---|
| 每次都要重新解釋專案架構 | Agent 自動載入相關記憶 |
| 同樣的 bug 踩兩次 | 踩坑教訓被記住,下次自動避開 |
| 「上次那個問題怎麼修的?」→ 翻對話紀錄 | 語意搜尋秒找到 |
| 換平台(Cursor → Cursor)就失去所有 context | 所有平台共享同一份記憶 |
| 記憶越積越多,找不到有用的 | 每日自動整理:過期歸檔、重複去除、AI 判斷相關性 |
| 特點 | 說明 |
|---|---|
| 免費 | Workers Free 方案包含 D1、Vectorize、Workers AI — 個人使用不花錢 |
| 全球部署 | 邊緣節點,哪裡用就哪裡快 |
| Serverless | 不用管 server、不用 Docker、不用 VPS |
| 安全 | OAuth 2.1 認證 + API 密鑰 + CORS 白名單 |
| AI 內建 | Workers AI 直接用 — embedding + 文字生成,不需要另外接 OpenAI |
前置條件: Cloudflare 帳號(免費)+ Node.js 18+ + Wrangler CLI(npm install -g wrangler)
# 1. 登入 Cloudflare(只需做一次)
wrangler login
# 2. Clone
git clone https://github.com/beach55607-max/mcp-memory-server.git
cd mcp-memory-server
# 3. 自動設定 + 部署
bash setup.sh
setup.sh 會自動完成:安裝依賴 → 建立 D1/Vectorize/KV → 產生 wrangler.toml → 設定 API 密鑰 → 執行 migration → 部署。
部署完成後你會看到:
你的 server 已上線:https://mcp-memory-server.你的子網域.workers.dev
MCP 端點:https://mcp-memory-server.你的子網域.workers.dev/mcp
設定 ALLOWED_ORIGINS,指定哪些網站可以連你的 server:
# 在 Cloudflare Dashboard → Workers → 你的 Worker → Settings → Variables
# 或直接改 wrangler.toml 後重新部署
ALLOWED_ORIGINS = "https://claude.ai,https://cursor.com"
| 什麼 | 自動程度 | 原理 | |-----
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