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Peon Mem

제작자: VineetV2버전 1.0.9i★ –i내 컴퓨터에서 실행
레지스트리 이름io.github.VineetV2/peon-mem

설치

개요

제작자가 쓴 설명(영어 원문)

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

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

  • 연결 방식: 내 컴퓨터에서 실행
  • 전송 방식: stdio
  • 카테고리: 검색 및 AI 기억

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

필요한 것

  • npmNode.js 설치(npx 명령어용)

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요

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

터미널에서 이 명령어를 실행하세요

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

실행하기 전에 빈 값을 채워 주세요.

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

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

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

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

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

직접 입력할 값

  • PEON_DAEMON_URL env
    Peon daemon address

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 GitHub 계정 VineetV2 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요

  • … 아직 점검 안 함

    계속 관리되고 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    라이선스 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • – 해당 없음

    엔드포인트 응답

    내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요

  • – 해당 없음

    OAuth로 로그인

    내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요

검색 및 AI 기억 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 7270개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 7270개 중 41%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 7270개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

Peon Mem, 안전한가요?

해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.0.9)은 2개월 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Context7, Codebase Memory, Exa

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Context7

제작자: upstash

Up-to-date docs for AI agents

컴퓨터 또는 클라우드★ 64,224MIT어제 업데이트
설치

Codebase Memory

제작자: DeusData

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

내 컴퓨터에서 실행★ 48,148MIT21일 전 업데이트
설치

Exa

제작자: exa-labs

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

클라우드에서 실행★ 5,213MIT지난달 업데이트
설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

🧠 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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