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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Peon Mem

作者:VineetV2版本 1.0.9i★ –i在你的电脑上运行
注册名称io.github.VineetV2/peon-mem

安装

概览

作者提供的说明(英文原文)

Local-first memory brain for AI coding agents: hooks capture sessions, beliefs injected per prompt.

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: 开发者工具

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

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": {
    "peon-mem": {
      "command": "npx",
      "args": [
        "-y",
        "peon-mem"
      ],
      "env": {
        "PEON_DAEMON_URL": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add peon-mem --env PEON_DAEMON_URL=your-value -- npx -y peon-mem

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": {
    "peon-mem": {
      "command": "npx",
      "args": [
        "-y",
        "peon-mem"
      ],
      "env": {
        "PEON_DAEMON_URL": "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": {
    "peon-mem": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "peon-mem"
      ],
      "env": {
        "PEON_DAEMON_URL": "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

  • PEON_DAEMON_URL env
    Peon daemon address

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 VineetV2 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“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 4900 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 4900 个服务器的 45% 更新
  • 基础检查结果等于或优于此分类中其他 4900 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

Peon Mem 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(1.0.9)于2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:GitHub, Desktop Commander, Cloudflare MCP

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

GitHub

作者:github

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

电脑或云端★ 34,245MIT4天前更新
安装

Desktop Commander

作者:wonderwhy-er

MCP server for terminal commands, file operations, and process management

在你的电脑上运行★ 10,225MIT16天前更新
安装

Cloudflare MCP

作者:cloudflare

Cloudflare MCP servers

在云端运行★ 4,446Apache-2.014个月前更新
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。

🧠 Peon — a memory brain for your AI coding agents

Local-first, hierarchical, self-improving memory for Claude Code, Codex, and any MCP client.

Your AI forgets everything between sessions. Peon doesn't. It records your sessions, uses an LLM to consolidate them into typed *beliefs*, and injects the relevant ones back into every prompt. It runs as a daemon on your machine, and nothing leaves it.

        PEON GLOBAL BRAIN            ← user-level facts & preferences, inherited everywhere

/ | \ project A project B project C ← rooted child brains (.peon/ in each project)

Why Peon

  • Hierarchical brains. One global parent brain holds who you are, your rules, and your tools. Each project gets an isolated child brain. Every injection carries both.
  • Two memory layers, honestly measured. Consolidated *beliefs* (decisions, preferences, facts, artifacts) give you the gist. An *episodic* verbatim layer recovers the exact details that lossy summaries drop. In my own LongMemEval run, raw-episodic recall scored 61% where belief-only scored 17% — self-measured, not an independent benchmark; reproduce it with npm run eval.
  • Automatic capture and injection. Claude Code hooks record messages and events, then inject a query-ranked memory block (with an ⚠ MOST RELEVANT headline) into every prompt. You never have to remember to save anything.
  • Cost-gated consolidation. An LLM distills sessions into beliefs only once enough new memory accumulates. It can supersede, merge, and flag conflicts. Nothing is destructively deleted.
  • Hybrid retrieval. Lexical and semantic RRF fusion, MMR diversity, reinforcement, and recency. Query embeddings are cached to disk, so repeat prompts cost nothing.
  • The Neural Universe. A live monitor at localhost:3737/monitor renders every belief as a star. Projects are galaxies, search makes matches flare, and autonomous curation pulses.
  • A daily self-audit (STL). Peon checks itself every day: what it recorded, what it injected, what failed, what consolidation did. Then it files a report with a verdict.
  • Eval-gated development. A committed results ledger (git SHA, qrels, and brain fingerprint per row) means retrieval changes are proven, not asserted. Negative results stay documented.
  • Local-first and locked down. Plain JSONL you can read, a loopback-only daemon with DNS-rebinding protection, secret redaction at the injection boundary, and path-traversal guards.

*The live monitor: 18k real beliefs rendered as stars. Type to make matching beliefs flare; click one to inspect it.*

*Ask the field: typing "wulver cluster" makes 400+ matching beliefs flare while the rest dim, and the camera flies to them.*

Why "Peon"?

The name comes from Indian offices. Every office had a peon, the person who walked desk to desk all day: collect a file from this table, note who needs what, carry it to the next table, remember where everything is. He wasn't the boss or the star, but the whole office quietly ran on him. Nothing moved without him, and he never forgot where anything was.

That's this framework, with AI. Peon walks between your sessions and your projects. It collects what happened at one desk (a session), files it in the right cabinet (a project brain), carries the relevant papers to the next desk before you ask (injection), and keeps the master ledger upstairs (the global brain). Quiet clerk. Perfect memory. The office runs on him.

How Peon differs from existing memory tools

Peonmem0Letta/MemGPTZep/Graphitiflat memory files (MEMORY.md)
Runs100% local daemoncloud or self-hostservercloud/serverlocal
Storagehuman-readable JSONL you can catvector DBDBgraph DBmarkdown
Memory modelbeliefs + verbatim episodic layerextracted factsself-edited blockstemporal knowledge graphprose
Hierarchyglobal parent brain → per-project child brains, inherited on every promptuser/agent/session scopesper-agentper-userper-project file
Captureautomatic via hooks (zero effort)SDK calls you writeagent-managedSDK callsagent must remember to write
Conflict handlingsupersede/merge, recoverable — never hard-deletesLLM may DELETEself-editinvalidationoverwrite
Exact recallepisodic layer regression-tested (61% vs 17% belief-only on LongMemEval, self-measured)gist onlygist onlygraph factswhatever was written
Observabilitylive Neural Universe monitor + daily self-audit (STL) + serve telemetrydashboard———
Verificationcommitted eval ledger; negative results keptvendor benchmarks—vendor benchmarks—

The short version: mem0 and Zep are memory platforms for products you build. Peon is memory for the coding agents you already use. It plugs into Claude Code or Codex in about five minutes, and you can watch it think and audit every number it claims.

Your agents share one brain

If you run more than one coding agent — Claude Code and Codex, say — they usually each live in their own bubble. Whatever you work out with one is gone when you switch to the other.

Point them at the same project and Peon dissolves that wall. Both agents resolve to the same .peon/ brain (Peon canonicalizes the project path, so the hook, a direct MCP call, and Codex all land on one store). So the memory flows between them:

  • Codex works out how your build pipeline runs and records it. Next time you open Claude Code in that repo, it's already in the injected context.
  • Claude Code hits a gotcha and files it. Codex sees it the moment it calls get_context or search_memory.
  • The global brain sits above both, so your preferences and rules follow you into every agent, in every project.

They aren't chatting in real time. It's a shared notebook both write in and both read from, so a decision made in one agent shows up in the other without you re-explaining it. One project, one memory, however many agents.

Quickstart

Requirements: Node 20+, macOS or Linux. An OpenRouter API key is recommended (consolidation + semantic embeddings); without one Peon still works lexical-only.

One line:

npm install -g peon-mem && peon-mem install

(no Node? curl -fsSL https://raw.githubusercontent.com/VineetV2/peon-mem/main/install.sh | bash)

The guided setup asks four things:

  1. Where your global brain lives (default: ~/Library/Application Support/Peon)
  2. Which LLM: OpenRouter (one key, any model) · OpenAI · Anthropic · Ollama (100% local & free) · or skip
  3. Installs the daemon as an auto-start service (launchd on macOS, systemd user unit on Linux)
  4. Detects your AI apps and wires the MCP server (plus hooks for Claude Code) into the ones you pick. Auto-configured: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, Windsurf, Cline, VS Code (Copilot MCP), Zed, LM Studio. Detected with in-app instructions: ChatGPT Desktop, Perplexity Desktop. Every touched config gets a .peon-backup.

That builds the package, starts the daemon as a service, wires your Claude Code hooks + MCP server (with a backup of your settings), and writes a config template. Then add your key to ~/Library/Application Support/Peon/.env and open the monitor. peon-mem install --dry-run shows every action first; peon-mem uninstall reverses it (memory data is never touched).

Or manually:

git clone https://github.com/VineetV2/peon-mem && cd peon-mem

npm install && npm run build node bin/peon-mem.mjs install --dry-run # inspect, then run without --dry-run

Create .env in the repo root:

OPENROUTER_API_KEY=sk-or-...

PEON_PROCESSING_MODEL=google/gemini-2.5-flash-lite # cheap + good enough (measured) PEON_EMBEDDING_MODEL=openai/text-embedding-3-small

Start the daemon (the installer prints a launchd/systemd recipe, or just):

node dist/daemon-cli.js              # serves 127.0.0.1:3737

Then wire your agent (the installer prints these filled in for your paths):

  • Claude Code: add the hook to ~/.claude/settings.json (SessionStart / UserPromptSubmit / SessionEnd → scripts/claude-peon-hook.mjs) and the MCP server (dist/index.js).
  • Codex / any MCP client: register dist/index.js as a stdio MCP server; 16 tools (start_session, get_context, search_memory, record_message, process_memory, …).

Open http://127.0.0.1:3737/monitor and watch your brain grow.

How it works

  1. Record. Hooks stream messages, events, and tool calls into /.peon/raw/ (append-only).
  2. Consolidate. Past a size gate, an LLM turns the session delta into typed belief records in .peon/brain/memories.jsonl (importance/confidence scores, entities, provenance pointers), reconciling against existing beliefs: supersede, merge, conflict-flag. Recoverable, never deleted.
  3. Retrieve + inject. On every prompt, beliefs are ranked (RRF lexical+semantic, MMR, reinforcement) and injected alongside episodic verbatim matches and inherited global beliefs.
  4. Self-curate. A background brain pass reinforces recalled beliefs, compresses stale clusters, and resolves duplicates. Every action is logged and undoable.
  5. Self-audit (STL). A daily job reports what was recorded, what was injected, what went wrong, and whether consolidation behaved, with serve-latency telemetry and a health verdict.

Full install (copy-paste)

1. Daemon (always-on, macOS launchd)
node scripts/install-peon.mjs           # prints everything below filled in for YOUR paths

Or manually — ~/Library/LaunchAgents/com.peon.daemon.plist:

<?xml version="1.0" encoding="UTF-8"?>

<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">

Label com.peon.daemon ProgramArguments /opt/homebrew/bin/node /ABSOLUTE/PATH/TO/peon/dist/daemon-cli.js

RunAtLoad KeepAlive

launchctl load ~/Library/LaunchAgents/com.peon.daemon.plist

curl http://127.0.0.1:3737/health # → {"ok":true}

Linux: the installer writes ~/.config/systemd/user/peon-mem.service and enables it. Manual equivalent: systemctl --user enable --now peon-mem.service, plus loginctl enable-linger $USER so it survives logout. (Linux support is young — issue #1 tracks real-machine reports.)

2. Claude Code — hooks (auto capture + injection)

Merge into ~/.claude/settings.json (replace the path):

{

"hooks": { "SessionStart": [{ "hooks": [{ "type": "command", "command": "node /ABSOLUTE/PATH/TO/peon/scripts/claude-peon-hook.mjs" }] }], "UserPromptSubmit": [{ "hooks": [{ "type": "command", "command": "node /ABSOLUTE/PATH/TO/peon/scripts/claude-peon-hook.mjs" }] }], "SessionEnd": [{ "hooks": [

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