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제작자가 쓴 설명(영어 원문)
Local-first AI identity for MCP coding tools. Lessons, decisions, and context you control.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
ENGRAM_MCP_STARTUP_SYNC, ENGRAM_TOOLS, PYTHONIOENCODING필요한 것
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": {
"piia-engram": {
"command": "uvx",
"args": [
"piia-engram",
"--transport",
"stdio"
],
"env": {
"ENGRAM_MCP_STARTUP_SYNC": "your-value",
"ENGRAM_TOOLS": "your-value",
"PYTHONIOENCODING": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add piia-engram --env ENGRAM_MCP_STARTUP_SYNC=your-value --env ENGRAM_TOOLS=your-value --env PYTHONIOENCODING=your-value -- uvx piia-engram --transport stdio실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"piia-engram": {
"command": "uvx",
"args": [
"piia-engram",
"--transport",
"stdio"
],
"env": {
"ENGRAM_MCP_STARTUP_SYNC": "your-value",
"ENGRAM_TOOLS": "your-value",
"PYTHONIOENCODING": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"piia-engram": {
"type": "stdio",
"command": "uvx",
"args": [
"piia-engram",
"--transport",
"stdio"
],
"env": {
"ENGRAM_MCP_STARTUP_SYNC": "your-value",
"ENGRAM_TOOLS": "your-value",
"PYTHONIOENCODING": "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.
ENGRAM_MCP_STARTUP_SYNC envENGRAM_TOOLS envPYTHONIOENCODING env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 9일 점검
레지스트리 이름이 GitHub 계정 Patdolitse 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
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.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(4.27.0)은 8일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: GitHub, Desktop Commander, Cloudflare MCP
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:↓ 주간 다운로드i★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Tell AI once who you are, how you work, and what "good" means. Claude Code, Codex, Cursor, Windsurf, and other MCP-compatible tools can start from the same AI work identity layer — local files you own, no cloud account, no hidden memory you cannot inspect.
Install · See It in Action · Supported Tools · MCP Tools · FAQ
ENGLISH | 中文
Listed in:
Also listed in: awesome-agents · Awesome-MCP-ZH · mcpservers.org · Cursor Directory · ModelScope · PulseMCP
TL;DR: piia-engram is a local-first personal AI identity layer. It helps multiple coding agents start from the same understanding of you: your preferences, quality bar, lessons learned, decisions, and project context. It is not an agent memory database; it is the user-owned layer above your tools.
Why not just use native memory? Claude Code, Codex, Cursor, and Windsurf are adding their own memories and rules. Those are useful, but they are scoped to one tool or workspace. piia-engram gives you one portable identity layer above them: local files you own, AI-proposed knowledge you review, and context that can follow you across tools.
Trust model in four lines:
pip, keep the core store on your machine.~/.engram/ as JSON/Markdown.ENGRAM_APPROVAL=strict to gate every write. "Verified" means accepted by you or by that policy, not re-checked against your current code.Want proof? See the live cross-tool continuity proof — a memory written by Claude Code, read back by Codex through one local store — or the one-command reproducible code demo.
You → "Help me refactor this auth module"
AI → "What language? What framework? What's your testing preference?"
AI → "Based on your preference for pytest + 90% coverage, and your lesson about always separating auth middleware from business logic (from the March incident), here's my approach..."
And you never have to take that on faith — Memory Lens (engram preview --html) shows exactly what any AI caller would receive, and what governance withheld, before anything is sent:
*Above: a real report from a demo store — 4 items exposed; an unreviewed staging note and a lesson containing a credential are withheld, with the secret shown as [REDACTED].*
pip install piia-engram && engram setup
The wizard auto-detects your AI tools — Claude Code, Cursor, Codex, Claude Desktop — lists the exact config files it will touch, and writes the MCP connection after a one-keystroke confirm (every write is backed up first; decline and nothing changes). It previews your identity card, then you restart your configured tool; the first conversation can load your approved identity and long-term knowledge through startup or search tools. (full walkthrough ↓)
Ask your coding agent to install Engram and inspect the plan before applying:
pip install piia-engram
engram setup --non-interactive --json engram setup --non-interactive --apply engram doctor --json
Setup asks no questions. Use --clients cursor,codex to limit clients and --lang zh|en for output language (default en). Without --apply, plan mode writes nothing to the Engram store, home directory or client configs. Python itself may use the system temporary directory. Apply configures MCP connections with backups, preserves existing tool modes, and never imports memories, writes identity/knowledge, or approves proposals. Restart configured clients; exit code 1 means a manual step remains. See llms.txt for agent instructions and the CLI and JSON contract for details.
Evidence levels follow the agent client validation runbook: L0 = discovery, L1 = protocol access, L2 = read/search behavior, L3 = A/B behavior gain, L4 = cross-client continuity, L5 = reproducible public evidence.
| Tool | Integration | Evidence status |
|---|---|---|
| Claude Code | MCP over stdio | L4 partial continuity proof (Claude Code -> Codex) |
| Codex | MCP over stdio | L4 partial continuity proof (Claude Code -> Codex) |
| Cursor | MCP over stdio | L2 setup/read-search evidence path |
| Claude Desktop | MCP over stdio | L1/L2 setup path; client-specific evidence pending |
| Hermes | MCP over stdio | L4 controlled CLI marker continuity; desktop and broad benchmark claims unverified |
| OpenClaw | SOUL.md / MEMORY.md / USER.md import and export | L3 static file-bridge evidence (static snapshot A/B only; live agent behavior unverified) |
| ChatGPT / Gemini / Kimi | Markdown identity card fallback | Usable |
| Windsurf | MCP over stdio | Expected to work |
| GitHub Copilot | MCP over stdio | Expected to work |
| Cline | MCP over stdio | Expected to work |
| Roo Code | MCP over stdio | Expected to work |
| Amazon Q | MCP over stdio | Expected to work |
| Augment | MCP over stdio | Expected to work |
| Zed | MCP over stdio | Expected to work |
| Trae | MCP over stdio | Expected to work |
| Tencent CodeBuddy | MCP over stdio | Expected to work |
These are current repository facts from docs/public-facts.json. Public registries and package badges update only during release/publish.
| Current repo / development facts | |
|---|---|
| Version frame | v4.27.0 (verified 2026-11-01; check PyPI and GitHub Releases for the latest published package) |
| Supported AI tools | 16 (evidence level varies by client; see Supported Tools and the validation runbook) |
| MCP tools | 19 Core (loaded by default) + 40 Advanced (opt-in via ENGRAM_TOOLS=all) |
| Knowledge types | 3 (lessons, decisions, playbooks) |
| Test suite | Unit + integration; run pytest tests/ to verify |
Lines in core.py | 1770 (facade; domain logic now lives in focused mixins — see architecture.md) |
| PBKDF2 iterations | 600,000 (OWASP 2023+ floor; legacy 100k still decrypts) |
| Encryption | Optional field-level AES-256-GCM for supported profile fields; local files are plaintext JSON/Markdown by default |
| Cold-start time | < 100 ms typical (local JSON, no network) |
| Network calls by default | One anonymous usage ping a day (engram telemetry off or DO_NOT_TRACK=1 turns it off); the engram command also checks PyPI for a newer version at most once a day in interactive terminals, and engram doctor checks on each run (ENGRAM_NO_UPDATE_CHECK=1 turns it off); identity and knowledge tools make none, except the optional read_web_content; remote telemetry and feedback require separate explicit opt-in and send counts only (see privacy details) |
Your AI forgets you every time you switch tools or start a new chat. piia-engram fixes the handoff.
Every time you open a new chat window, switch from Claude Code to Codex, update your AI tool, or move into a different project, you're back to zero:
This happens because AI memory today is locked inside each platform. It belongs to the tool, not to you. The tool updates, resets, or gets replaced — and your context disappears with it.
piia-engram gives you a personal identity layer that lives on your machine, independent of any AI tool. You tell it once who you are, how you work, and what you've learned. MCP-compatible tools can read the same approved identity and long-term knowledge. New chat, new tool, new version — your identity stays portable.
piia-engram is not an agent memory database. Tools like Mem0, Zep, and Letta store task context and session history for AI agents. piia-engram stores *who you are as a person* — your identity, preferences, hard-won lessons, and key decisions. It's a different layer: not what happened in a task, but who is behind every task.
| Without piia-engram | With piia-engram |
|---|---|
| New chat window = start from zero | Configured conversations can load your approved identity and long-term knowledge |
| AI tool updates and your preferences vanish | Your identity lives on your machine, survives any update |
| Switching tools loses accumulated context | Claude Code, Codex, and Cursor read the same memory |
| Past mistakes get repeated | Lessons learned follow you across tools and sessions |
| Memory is locked inside one product | Data stays local, editable, and portable |
piia-engram is built for developers who use multiple AI coding tools and are tired of re-explaining themselves.
If you switch between Claude Code, Codex, and Cursor — your code standards, architecture decisions, and hard-won lessons reset every time. piia-engram makes eve
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요