Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Coding agent memory — one local MCP server for every project. Warns before repeating failed fixes.
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.
필요한 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": {
"projectmem": {
"command": "uvx",
"args": [
"projectmem"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add projectmem -- uvx projectmem프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"projectmem": {
"command": "uvx",
"args": [
"projectmem"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"projectmem": {
"type": "stdio",
"command": "uvx",
"args": [
"projectmem"
]
}
}
}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.
이 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 6일 점검
레지스트리 이름이 GitHub 계정 riponcm 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(0.3.5)은 6일 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: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
🎉 v0.3.5 is out — precheck recognises a file however its path is spelled, and the summary stays small even when entries are long. See what changed →
We don't make AI smarter. We make it experienced. Coding agent memory — the local-first memory + judgment layer for AI coding agents. One MCP server for every project. Stop re-reading your project every session. Stop repeating yesterday's bug.
Website • Guide • Demo • Changelog • Paper
https://github.com/user-attachments/assets/e055988e-7253-4ba9-92fc-95d3d4bcd763
pjm visualize — every case your project solved, what failed on the way, and what it saved. Generated locally from .projectmem/events.jsonl .
## 🚀 Start here — five minutes, once
*Five minutes if you follow along here. Want to be shown instead — every
command, the exact output it prints back, and the dashboards at the end?
Take [the complete setup guide](https://projectmem.dev/blog/projectmem-complete-guide-ai-coding-agent-memory).*
New to projectmem, or upgrading from 0.1.x / 0.2.x? Since 0.3.0 one MCP
server serves every project, so this is the last time you configure anything.
1. Install or update
`bash
pip install -U projectmem
`
2. Find the projects you already have
`bash
pjm doctor
`
It looks where code lives —
~/Developer,~/code,~/projects, your cloud
folders, and every drive on Windows — and lists projects with memory that
aren't registered yet. Anything it missed, add by hand:
`bash
pjm project register "/Users/you/Developer/repos/ossdrop"
`
3. Register them
`bash
pjm doctor --fix
`
4. Point your AI at all of them with one config
`json
"mcpServers": {
"projectmem": {
"command": "/absolute/path/to/python",
"args": ["-m", "projectmem.mcp_server"]
}
}
`
No
--root, nocwd— that's what makes it serve everything. Per-client
instructions (Claude Desktop, Claude Code, Cursor, Antigravity, Codex) are in
MCP Integration;
pjm initprints this block
with your own Python path filled in. Then fully restart the client — MCP
servers only load on a cold start.
5. Check your work
`bash
pjm doctor
`
Add
--onlineif you also want it to tell you when a newer projectmem is out
— projectmem makes no network calls otherwise, and
--autoturns that into a
once-a-day check if you prefer.
Run it again after editing the config. It flags any client still pinned to a
single repo — the most common reason a new project is invisible to your agent.
All green? You're done. From here on it is one command per repo:
`bash
pjm init
`
Your agent reads what the project already learned instead of rediscovering it,
and writes down what it finds. Fewer tokens, no repeated dead ends, memory that
outlives the session.
Coding agent memory is a persistent record of what happened while building a project — the issues hit, the approaches attempted, the fixes that worked and the decisions made — stored so an AI coding agent can read it at the start of a new session. Without it every session begins from zero.
projectmem is an open-source agent memory layer built for that job. It is local-first: memory lives in a plain .projectmem/ directory inside your repository, with no cloud, no account and no telemetry — the only network call it can make is an update check you turn on yourself. A native MCP server exposes 17 tools to Claude Code, Claude Desktop, Cursor, Antigravity and Codex, so your agent reads memory and logs its work on its own.
Unlike chat-history memory tools, projectmem stores typed events — issues, attempts, fixes, decisions, notes — which is what makes its signature feature possible: a pre-commit warning that fires *before* you repeat an approach that already failed in this project.
pip install projectmem
cd your-project && pjm init
Full screen-recorded tutorial- watch on YouTube
| Doc | What's in it |
|---|---|
| [Complete setup guide](https://projectmem.dev/blog/projectmem-complete-guide-ai-coding-agent-memory) | The full walkthrough on the web — install, MCP setup per client, pjm doctor, your first logged issue, and both dashboards. Every terminal output is captured from a real run. |
| [TUTORIAL.md](https://github.com/riponcm/projectmem/blob/main/TUTORIAL.md) | 15-minute step-by-step walkthrough — set up projectmem on your own project, watch the lifecycle, see the pre-commit warning fire. |
| [CHANGELOG.md](https://github.com/riponcm/projectmem/blob/main/CHANGELOG.md) | Release history. Latest: v0.3.5 — precheck matches every spelling of a path, and long entries no longer bloat the summary. |
| [Research paper (arXiv:2606.12329)](https://arxiv.org/abs/2606.12329) | *PROJECTMEM: A Local-First, Event-Sourced Memory and Judgment Layer for AI Coding Agents* — the peer-readable version: design, Memory-as-Governance framing, capability comparison, and the 207-event dogfooding study. |
| [LICENSE](https://github.com/riponcm/projectmem/blob/main/LICENSE) | MIT |
Every new AI session starts from zero. Claude, Cursor, Aider — they all forget yesterday's decisions, repeat failed debugging attempts, and burn millions of tokens reconstructing context from raw source files.
The model isn't the problem. The architecture is. Stateless models need a memory cortex.
projectmem is the local-first memory + judgment layer that sits above your AI tools. It captures every failed attempt, decision, and gotcha — then injects that experience back into future AI sessions. Git tracks *what* changed. projectmem tracks *why* it changed, what was tried, and what failed.
First time here? → [The complete setup guide](https://projectmem.dev/blog/projectmem-complete-guide-ai-coding-agent-memory)
walks the whole path end to end: install, connecting Claude Desktop, Claude Code,
Cursor, Codex or Antigravity, checking it with
pjm doctor, and reading your
memory back through the dashboards — with the real terminal output at every step.
Three commands to a project that remembers:
pip install projectmem
cd your-project pjm init
That's it. pjm init installs three git hooks (pre-commit warnings, post-commit classification, post-merge tracking), auto-starts a real-time file watcher, inherits cross-project memory if available, and creates .projectmem/. Capture is active from minute one.
The canonical command is
projectmem. Apjmalias is installed for speed.
Precheck recognises a file however its path is spelled. Events store project-relative paths, so asking about ./src/auth.py, an absolute path, a path through a symlinked folder or a Windows C:\ path matched nothing, and precheck called a file with known failures "Safe to modify". Every spelling now gets the same warnings, and checking is faster on large logs. get_issue("1") and get_issue("#1") find issue 0001. (#26)
Long entries no longer bloat the summary. 0.3.4 capped how many entries the summary shows, not how long each one is. Records are now clipped at 300 characters, and a fixed issue takes one line. On a real 238-event project the summary went from 8,974 tokens to 3,458. (#29, #30)
Upgrading? Run `pjm init` once in each project. The instructions now ask agents for shorter records, and pjm init refreshes AI_INSTRUCTIONS.md, keeping your previous copy as AI_INSTRUCTIONS.md.bak.
The #26 fixes were contributed by @vishalhabib99, and #29 was reported and fixed by @bigfree.
The summary no longer grows forever. Notes were capped, but Recent issues and Decisions listed everything ever logged, so on an aged project reading the memory cost more than reading the code. Every open issue is still shown — the newest 20 in full, older ones by id — while fixed issues are capped at the newest 10 and decisions at the newest 15, each with a line saying what was left out and where to find it. On a test project with 25 issues and 60 decisions the summary went from about 2,900 tokens to about 1,100. (#19)
Commits are filed under the code they change. Auto-capture used the first changed path in git's sort order, which was usually the regenerated .projectmem/summary.md — so valid memories were flagged stale and the real file lost its history. The location is now the source file the commit is about, with deletions, renames, merges and a repository's first commit handled. (#20)
Stale warnings no longer depend on your time zone. A 0.3.3 speed-up compared git's local-time commit dates with UTC event times as text: west of UTC, recent stale memories were never flagged; east of UTC, fresh ones were flagged at once. Both sides are compared in UTC now, and events already filed under .projectmem/ stop warning without your log being rewritten.
*
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요