原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Project Memory MCP

作者:kaaustubh版本 1.6.0i★ –i在你的电脑上运行
注册名称io.github.kaaustubh/project-memory-mcp

安装

概览

作者提供的说明(英文原文)

Persistent memory for AI coding agents — past bugs, decisions, and your corrections, in your repo.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: PROJECT_MEMORY_ROOT

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "project-memory": {
      "command": "npx",
      "args": [
        "-y",
        "@kaaustubh/project-memory-mcp"
      ],
      "env": {
        "PROJECT_MEMORY_ROOT": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add project-memory --env PROJECT_MEMORY_ROOT=your-value -- npx -y @kaaustubh/project-memory-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "project-memory": {
      "command": "npx",
      "args": [
        "-y",
        "@kaaustubh/project-memory-mcp"
      ],
      "env": {
        "PROJECT_MEMORY_ROOT": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "project-memory": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@kaaustubh/project-memory-mcp"
      ],
      "env": {
        "PROJECT_MEMORY_ROOT": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • PROJECT_MEMORY_ROOT env
    Absolute path to the folder that holds your projects (the memory root). Defaults to the parent of the script if unset, so set it when running via npx.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 kaaustubh 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 7259 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7259 个服务器的 19% 更新
  • 基础检查结果等于或优于此分类中其他 7259 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Project Memory MCP 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.6.0)于4个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT昨天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT20天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

project-memory MCP server

A small, local MCP server that gives AI agents (Claude Code, Cursor, VS Code / GitHub Copilot, …) a shared, persistent memory of the projects in a code folder — what each project is, decisions made, and every bug/issue faced during development.

It is stateless: every tool reads/writes plain files on disk, so multiple clients (and multiple machines) share one source of truth.

The model

LayerLives inAuto-loaded into context?For
Project memory /AGENTS.md✅ yes (via CLAUDE.md → @AGENTS.md)identity, stack, run cmds, concise decisions/learnings — keep lean
Issue log /issues.jsonl❌ nohigh-volume bug/issue history — fetched on demand

Design rule: durable, low-volume facts go in AGENTS.md (auto-loaded). High-volume history (bugs) goes in issues.jsonl (queried via search_issues). This keeps the always-loaded context small while keeping everything searchable.

Works even where MCP is locked down

Some orgs disable third-party MCP servers via policy (e.g. GitHub Copilot's MCP allowlist enforcement). Because the memory is plain files, not a service, the core value survives that:

  • The memory itself is just files. AGENTS.md is auto-loaded by the editor reading it — no MCP call involved — so a project's identity, decisions, learnings, and preferences still land in the agent's context.
  • The policy is Copilot-scoped and per-client. It doesn't affect the same server in Claude Code or Cursor, and orgs running *allowlist / registry-only* mode can permit it — this server is published to the official MCP Registry (io.github.kaaustubh/project-memory-mcp).

Only the interactive tools (log_issue, search_issues, …) go over the MCP channel; the file-based memory keeps working without it.

Tools

  • list_projects, get_project, search_memory — read project memory
  • append_decision, append_learning — append a dated bullet to AGENTS.md
  • remember_preference — turn a correction / stated habit into a remembered pattern (## Preferences in the root AGENTS.md for a global habit, or a project's for a local one); rides the auto-load, so it comes back next session
  • log_issue — record a bug/problem → issues.jsonl
  • search_issues — "have we hit this before?" across all projects (field-scoped; optional tags filter)
  • list_open_issues, resolve_issue — track / close bugs
  • sync_registry — reconcile the root AGENTS.md projects table with what's on disk (adds rows for new projects, flags stale ones)
  • find_by_file — given a file path, surface the issues + decisions/learnings that touch it ("why is this code like this?")
  • start_initiative, get_initiative, list_initiatives, update_initiative — track a named, multi-session effort (a codename, a plan, an evolving todo list) so it's resumable from any future session by name, not just within the one that started it; see Initiatives below
  • check_in, check_out — stamp the start/end of the working day and record a standup summary composed from evidence harvested off disk (git commits across every repo, uncommitted WIP, memory writes, initiative progress); the next morning's check_in hands the summary back — that's your standup. Print it any time, no agent needed: npx -y @kaaustubh/project-memory-mcp standup

You don't call these directly — you talk to your agent in natural language and it picks

the tool. See Using it day to day below for what to actually say.

Using it day to day

Most of it runs itself: opening a project auto-loads its AGENTS.md (the agent already knows the project), and capture is proactive (plus the optional Stop hook). Your job is mainly to pull memory at the right moments. Just talk to your agent:

WhenSay something likeWhat fires
Before debugging anything*"Have we hit this before? "*search_issues across all projects
Starting something you've done elsewhere*"How did I do Stripe webhook verification in any project?"*search_memory (cross-project)
Landing on confusing code*"Why is index.js like this? Check the memory."*find_by_file
You made a real decision / fixed a real bug*(nothing — it logs on its own and tells you)*append_decision / log_issue
You correct how the agent works*"No, always run the typecheck before committing — remember that."*remember_preference (global or per-project)
Triage*"What's still open across my projects?"*list_open_issues
A bug is fixed*"Resolve pulse_stripe-004 — fixed by …"*resolve_issue
Added a new project*"Sync the registry."*sync_registry

The one habit that matters: make *"have we hit this before?"* reflexive before every debugging session. That's where a memory tool earns its keep; the rest the system handles.

Capture is confirming, not silent — when the agent logs something it tells you in one line. Correct it freely: *"don't log that"*, or *"actually, log this too."*

Escape hatches: PROJECT_MEMORY_HOOK=off silences the Stop hook for one session; uninstall-hook removes it entirely.

Install (npm — recommended)

From your code/projects folder, run:

cd ~/code            # the folder that holds your projects

npx -y @kaaustubh/project-memory-mcp install

That registers the server, using the current directory as your projects root, with every client that has an MCP config location on this machine:

ClientConfig written
Claude Codeuser scope, via claude mcp add
Cursor~/.cursor/mcp.json
VS Code / GitHub Copilot Chatuser-profile mcp.json (applies to every workspace)
GitHub Copilot CLI~/.copilot/mcp-config.json (or $COPILOT_HOME)
JetBrains Copilot plugin (IntelliJ, PyCharm, WebStorm, …)~/.config/github-copilot/intellij/mcp.json
Visual Studio (Windows)%USERPROFILE%\.mcp.json — global, all solutions
Kimi Code CLI~/.kimi-code/mcp.json (or $KIMI_CODE_HOME)
Gemini CLI~/.gemini/settings.json
OpenAI Codex CLI~/.codex/config.toml (the only non-JSON client — merged as TOML)
Windsurf~/.codeium/windsurf/mcp_config.json

Each write merges into the existing file (other MCP servers you've already configured are left alone) and is independently best-effort — a client that isn't installed on this machine is silently skipped, the rest still get registered. Restart whichever app(s) you use, then ask your agent *"set up project memory for this folder"* to scaffold AGENTS.md for each project.

Copilot surfaces (VS Code, CLI, JetBrains, Visual Studio): tools only run in

Agent mode, and config changes need a restart to take effect.

No clone, no global install — the MCP config just runs npx, which fetches and runs

the latest version on demand.

Team memory (beta signup): want this memory shared across your team instead of

just your machine? Register your interest: https://github.com/kaaustubh/project-memory-mcp/issues/1

From source instead
git clone https://github.com/kaaustubh/project-memory-mcp.git ~/code/.memory-server

cd ~/code/.memory-server && ./install.sh

How it works (after install)

A common question: *"once I install it, does it just start doing things?"* Not quite — the server is passive. Here's the actual flow:

  1. Restart your editor. MCP servers are loaded at startup, so the server only becomes available the next time you launch Claude Code / Cursor / VS Code.
  2. Push layer (automatic, not the server): when you open a project, the editor reads AGENTS.md (via CLAUDE.md → @AGENTS.md) into the model's context for you. This is why the agent "just knows" what your project is — it's a built-in editor feature.
  3. Pull layer (the server, on request): the server announces its tools and then waits. It does nothing on its own. The agent calls a tool only when it's relevant — e.g. you say *"log this bug"* or *"have we hit this before?"*, or the model decides a tool is useful. There's no background process or scanning.

Day one is empty. A fresh setup has no AGENTS.md files yet, so the auto-load has

nothing to load and log_issue will refuse until a project's memory exists. Bootstrap

once by asking your agent: *"set up project memory for this folder"* — it creates the

AGENTS.md files. After that, everything works.

In short: a convention (auto-loaded files) + a tool the agent chooses to use + a one-time setup. No magic, no daemon.

Proactive capture (you don't have to say "log this")

The server ships a standing capture policy (sent to the client on connect, plus directive tool descriptions), so the agent records things on its own instead of waiting for you to ask:

  • Before debugging a reported error → it checks search_issues for a prior fix.
  • After fixing a non-trivial bug → it calls log_issue.
  • After a real decision or a durable gotcha → append_decision / append_learning.
  • After you correct how it works or state a habit → remember_preference, so the one-time correction becomes a pattern it brings back next session.

It's proactive but not silent: the agent tells you in one line what it recorded, asks when unsure rather than logging noise, and skips trivia and secrets. You can always override — "log this", or "don't bother". The standing policy is best-effort (it depends on the model following it); for a hard guarantee, add the opt-in Stop hook below.

Guaranteed capture (opt-in Stop hook)

The standing policy can be forgotten mid-session. The Stop hook makes capture non-optional: when the agent tries to end a turn, it runs once and blocks the stop to ask for one capture pass when either (a) real work happened (file edits or a commit) and nothing was written to project memory, or (b) you corrected how it works and no preference was saved. If memory was already written, or nothing changed and you didn't correct it, the hook stays silent and lets the turn end.

npx -y @kaaustubh/project-memory-mcp install-hook    # turn it on (then restart Claude Code)

npx -y @kaaustubh/project-memory-mcp uninstall-hook # turn it off

  • Off by default — plain install does not add it; you enable it explicitly.
  • No loops — it fires at most once per turn (guarded by stop_hook_active), then lets the agent stop.
  • Per-session kill switch — set PROJECT_MEMORY_HOOK=off to disable without uninstalling.
  • Cost — it adds one extra model turn only on sessions that changed code but logged nothing, or where you corrected the agent and no preference was saved; silent otherwise.

Automatic recall (opt-in UserPromptSubmit hook)

Capture is only half the loop — the other half is *remembering to look*. The recall hook closes it: every time you submit a prompt, it matches your request against your issue history and decisions/learnings/preferences, and silently injects the strongest hits as context. So a prior fix or decision surfaces without you (or the agent) remembering to search — the "have we hit this before?" habit becomes automatic.

npx -y @kaaustubh/project-memory-mcp install-recall    # turn it on (then restart Claude Code)

npx -y @kaaustubh/project-memory-mcp uninstall-recall # turn it off

  • Semantic matching (when available) — if the optional embeddings model (@xenova/transformers) is installed, recall matches by meaning, so *"the build is broken"* still surfaces an issue logged as *"compile failure"* even

只显示了开头部分;其余内容请在仓库中阅读

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