
Mindpm
io.github.umitkavala由 GitHub 帳號 umitkavala 發布v3.2.0更新於 Oct 24, 2026
Project memory and a control plane for AI coding agents.
概覽
本機 MCP 伺服器,為 AI 編碼代理提供以 SQLite 儲存的專案記憶,記錄任務、決策、筆記與工作階段,並附帶看板。
- 可以做什麼
- 記錄與查詢任務、規格、驗收條件、優先順序與阻擋項目
- 保存決策及其理由和被否決的方案,以及架構、錯誤、慣例等筆記
- 開始與結束工作階段,讓新的對話接著上次進度繼續
- 把附規格的任務交給編碼代理,以認領與租約避免平行代理互相衝突,並記錄每次嘗試
- 在內建看板上驗收提交的工作,可選的驗證器會先重跑檢查
- 適用情境
- 適合跨多次獨立 AI 對話推進同一個專案、希望助理不必重複說明就能接上脈絡的情境,也適合多個編碼代理共用同一份任務清單而需要協調時。
- 執行需求
- 以 stdio 在本機執行,通常透過 npx 直接啟動,不需事先安裝。需要一個 SQLite 資料庫檔案,由 MINDPM_DB_PATH 指定(預設位於使用者家目錄下)。可選的 MINDPM_HOST 與 MINDPM_PORT 用來設定內建看板,預設在 localhost 的 3131 埠提供。僅支援桌面版 MCP 用戶端。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Mindpm,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
mindpm
Project memory and a control plane for AI coding agents.
mindpm is an MCP (Model Context Protocol) server that gives LLMs a SQLite-backed brain for your projects. It tracks tasks, decisions, architecture notes, and session context — so every new conversation picks up exactly where you left off. It also hands specced tasks to coding agents, keeps parallel agents from colliding, and only counts work as done once a human has accepted it. For agents that run unattended, an optional verifier reruns the checks itself first.
The Problem
Every new LLM chat starts from zero:
- "Let me remind you about my project..."
- "Last time we decided to use Redis for..."
- "Where did we leave off?"
The Solution
mindpm persists your project state in a local SQLite database. The LLM reads and writes to it via MCP tools. No chat history needed. No memory features needed.
What It Tracks
- Tasks, specs and acceptance criteria, with handoff statuses, priorities and blockers
- Decisions: what was decided, why, and what was rejected
- Notes and context: architecture, bugs, ideas, tech stack, conventions
- Sessions: what was done and what's next, plus a brief of what changed while you were away
- Agent attempts: every run on a task, and what the next attempt should avoid
Quick start
That's Claude Code, and npx fetches mindpm, so there's nothing to install first. Claude Desktop, Cursor, VS Code, Cline and Windsurf use the same JSON config in a different file. Then just talk about your project. The LLM calls start_session to load its context, records tasks, decisions and notes as you go, and calls end_session to save what's next. A Kanban board runs at http://localhost:3131.
How it works
Everything stays on your machine, in one SQLite file (~/.mindpm/memory.db by default). mindpm can also hand specced tasks to coding agents with no conversation context: claims with leases keep parallel agents from colliding, and you accept submitted work on the board. For agents that run unattended, an optional verifier reruns the checks on each submitted commit first.
Security: mindpm has no user accounts and can't stop a process on your own machine. An agent with a shell can call the board's routes as you or edit the database directly. Read the security model before you let agents run unattended.
Documentation
Full documentation: https://umitkavala.github.io/mindpm/
- Setup: every MCP client, agent instructions for any LLM, storage
- Kanban board: lanes, accepting work, network binding and WSL
- Session brief: what changed while you were away
- Agent execution: lifecycle, specs, claims and briefs
- Advanced: unattended agents and verification
- Security model
- MCP tools
- Development
- Changelog
License
MIT
來源:README.md,提交 4c194fd
工具
0版本歷史
3- v3.2.0最新Oct 5, 2026
- v3.1.1Oct 5, 2026
- v1.2.41Sep 16, 2026
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