GitHub
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제작자가 쓴 설명(영어 원문)
Cross-agent handoff: the next coding agent starts from the last one's facts, not a blank page.
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.
REMEMBRA_API_KEY, REMEMBRA_URL, REMEMBRA_AGENT_ID비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
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": {
"remembra": {
"command": "uvx",
"args": [
"remembra-mcp"
],
"env": {
"REMEMBRA_API_KEY": "your-value",
"REMEMBRA_URL": "your-value",
"REMEMBRA_AGENT_ID": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add remembra --env REMEMBRA_API_KEY=your-value --env REMEMBRA_URL=your-value --env REMEMBRA_AGENT_ID=your-value -- uvx remembra-mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"remembra": {
"command": "uvx",
"args": [
"remembra-mcp"
],
"env": {
"REMEMBRA_API_KEY": "your-value",
"REMEMBRA_URL": "your-value",
"REMEMBRA_AGENT_ID": "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": {
"remembra": {
"type": "stdio",
"command": "uvx",
"args": [
"remembra-mcp"
],
"env": {
"REMEMBRA_API_KEY": "your-value",
"REMEMBRA_URL": "your-value",
"REMEMBRA_AGENT_ID": "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.
REMEMBRA_AGENT_ID 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 7일 점검
레지스트리 이름이 GitHub 계정 remembra-ai 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.
입력해야 할 값: REMEMBRA_API_KEY, REMEMBRA_URL
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(0.17.5)은 13일 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:★ 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
Cloudflare MCP servers
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Remembra Relay
One agent stops. The next one already knows.
When a connected agent's session ends, Remembra Relay saves a handoff (a session that did nothing leaves none).
With the session hooks it is built from git and, for Claude Code and Codex, the session transcript.
An agent that closes through MCP reports its own facts, marked unverified.
The next agent, on another machine, from another vendor, or next week, starts from it.
Website • Relay guide • Docs • Changelog • Discord
First get a free key at app.remembra.dev, then run:
pipx install --force 'remembra[mcp]>=0.16'
remembra-install --all remembra-relay connect --apply
remembra-install asks for the key at a hidden prompt (or reads REMEMBRA_API_KEY) and shows its changes before it writes. connect --apply writes the hooks and keeps a backup of each file; run remembra-relay connect alone first to see every change without writing. Codex runs the hooks only after you trust them: Settings > Hooks > Trust in the Codex app, or /hooks in the Codex CLI. When a hook's command changes, Codex skips it until you trust it again. Hosting the server yourself? Add --url to remembra-install. remembra-relay ships in remembra 0.16.0.
Handoffs not arriving? remembra-relay doctor says where the baton dropped, from this machine's files and your trail, with one fix per problem; it only reads. Inside your agent the local MCP server has the same checks as read-only tools: remembra_doctor, remembra_setup (the install steps for this machine) and remembra_help. See Doctor.
Claude Code finished a session and wrote in its summary that the work was done and pushed. Git disagreed. The next agent's brief includes this line:
Last session: claude-code (key-verified), 12m ago, on feat/pdf-export@a41f2c9: done: a41f2c9 Add PDF export for invoices; 77c01aa Embed fonts in exported PDFs; tests passing: pytest tests/test_pdf.py (12 passed); changed 3 file(s): invoices/pdf.py, invoices/fonts.py, tests/test_pdf.py / NOT done: 2 commit(s) not pushed to origin/feat/pdf-export / failing: none / next (derived from the recorded facts): push 2 commit(s) to origin/feat/pdf-export (facts reported as collected by remembra-relay from git and the session transcript (not checked)) (the agent's summary contradicts these recorded facts)
With the session hooks, remembra-relay builds the done, not done and failing sections from git and, for Claude Code and Codex, the session's test runs, never from an LLM. The server does not check where the facts came from; the brief says they were reported by remembra-relay. The agent's own summary is optional; it is checked against those facts and shown as unverified, or, as here, contradicted. A handoff written through the close_session MCP tool holds the facts the agent declares, labeled "declared by the agent (not checked)".
remembra-relay close reads the branch, commits, changed and uncommitted files and unpushed commits from git, and, for Claude Code and Codex, the commands, test runs and open items in the local transcript (Codex's is its rollout file). The transcript itself stays on your machine. Secrets that match Remembra's patterns are redacted from what is sent.remembra-relay brief (run by the verified session hooks) or the session_brief MCP tool (any MCP agent can call it) gives the agent who worked last, what is done, what is failing and the next step. The text brief is capped at about 1,500 tokens (6,000 characters). session_brief returns only that text with compact=true; by default it also returns the full brief as JSON, which is larger. Everything another agent recorded is wrapped as untrusted data.remembra-relay trail, or the Trail page in the dashboard. A git log for your agents.The same repository on a laptop, a server or in a worktree is one project, because it is identified by its git remote. Give each agent its own scoped key and its handoffs show as key-verified.
| Agent | Session hooks | How it reads and writes handoffs today |
|---|---|---|
| Claude Code | verified | Hooks: brief at start, close at end, with test results from the transcript |
| Codex | verified (codex-cli 0.155.0-alpha.16.4, a prerelease) | Hooks: brief at start, close at end, with commands and test runs from the rollout; trust them in Codex (Settings > Hooks, or /hooks in the CLI), and again when one changes |
| Gemini CLI | verified (Gemini CLI 0.61.0) | Hooks: brief at start (after /clear, with the first prompt), close at end; they run only in folders you trust |
| Qwen Code | verified (Qwen Code 0.24.6) | Hooks: brief at start, close at end, on a rate-limit or billing stop and before /compress; qwen -p writes no handoff |
| Kimi Code | verified (Kimi Code 2.1.1) | Hooks: brief with the first prompt, close when the TUI exits; kimi -p writes no handoff |
| Cursor | unverified | MCP tools (session_brief, close_session) |
| Any other MCP agent | none | MCP tools |
Claude Code's and Codex's session hooks are verified (Codex with codex-cli 0.155.0-alpha.16.4, a prerelease, and the same tests also pass on the stable 0.157.1). The Gemini CLI, Qwen Code and Kimi Code hooks are verified too: each was run against the real tool at the version in the table, with a local stand-in for the model, and put the brief in the model's request and posted the handoff; other versions have not been run. The Cursor hooks are unverified: Cursor's own hook runner ran them, but no logged-in Cursor session has yet. connect leaves them out unless you add --include-unverified. Until they are tested, Cursor reads the brief and writes its handoff through Remembra's MCP tools, as does any MCP agent.
Several agents in one repository at once, without one undoing another's work. Name the areas of the repo in .remembra/zones.yml and commit it on the default branch:
version: 1
zones: api: include: ["src/api/"] web: include: ["src/web/"]
Then, at a terminal (it shows every change and asks before writing):
remembra-crew connect --apply # Claude Code
remembra-crew connect --agent codex --include-unverified --apply remembra-crew verify --agent codex # one round trip on your machine; Codex then enforces
The first agent to write in a zone holds it. Another agent's write there is stopped before it happens and the agent is told who holds it; it can ask for a handover with crew_say, or you hand it over from the dashboard.
| Agent | Writes to a held zone |
|---|---|
| Claude Code | stopped before every write (hooks verified) |
| Codex | stopped after remembra-crew verify --agent codex passes: shell commands and every file an apply_patch names (checked live on codex-cli 0.157.1) |
| Gemini CLI, Qwen Code, Kimi Code | stopped once verify passes on your machine; until then, read-only fence |
| Cursor and other agents | read-only fence in their own worktree; MCP-only agents are advisory |
Git hooks (connect --git-hooks) also stop a commit or push that touches a held zone, for every agent. The honest limit: these local layers stop cooperating agents' mistakes, not a deliberately hostile agent on the same machine. Crew mode needs a server that runs it (REMEMBRA_CREW_MODE; on for Remembra Cloud). The guide is Crew mode.
| Remembra Relay | Vendor memory (Claude Code, Codex, Copilot, Windsurf) | Local handoff tools | Memory APIs (Mem0, Zep, Letta) | |
|---|---|---|---|---|
| Works across machines | Yes, by git remote | Mostly no | No | Yes |
| Works across vendors | Yes | No, one vendor each | Yes | Through their API |
| Handoff facts from git | Yes, with the summary checked | No | Transcript or diff | No |
| Durable trail of sessions | Yes | No | No | No |
| Enforced coordination between agents | Crew mode (Claude Code; Codex once verified) | Claude-only agent teams | No | No |
Details, with a source and date, for claude-mem, agentmemory, the local handoff tools and Claude Code's own features: Remembra and other handoff tools. claude-mem and agentmemory are larger projects that also carry memory between sessions; the comparison says where each is the better pick.
Handoffs, briefs, the inbox, the trail and search are free on every plan. Remembra Cloud: Free, Solo $12/mo, Pro $29/mo, Team $15/seat/mo (pricing). Self-hosting is free under the MIT license.
Remembra Relay runs on Remembra's memory layer, which you can also use directly: store facts, recall them by meaning, and let it pull out the people, projects and relationships in them.
from remembra import Memory
memory = Memory(user_id="user_123") memory.store("Had a meeting with Sarah from Acme Corp. She prefers email over Slack.") result = memory.recall("How should I contact Sarah?") print(result.context)
Since v0.16.0 the memory layer also keeps the exact text that facts were derived from and points each fact back to it. By default a fact that does not match its source is not stored: the store response lists it under dropped_facts. With REMEMBRA_GROUNDING_ACTION=flag such a fact is stored and marked unverified instead.
curl -sSL https://raw.githubusercontent.com/remembra-ai/remembra/main/quickstart.sh | bash
This starts Remembra, Qdrant and Ollama locally, with auth off and local embeddings, so the server needs no API key. The first start downloads the images and the embedding model, so how long it takes depends on your connection.
Or with Docker Compose directly:
git clone https://github.com/remembra-ai/remembra && cd remembra
docker compose -f docker-compose.quickstart.yml up -d
Try it:
# Store a memory
curl -X POST http://localhost:8787/api/v1/memories \ -H "Content-Type: application/json" \ -d '{"content": "Alice is CEO of Acme Corp", "user_id": "demo"}'
curl -X POST http://localhost:8787/api/v1/memories/recall \ -H "Content-Type: application/json" \ -d '{"query": "Who runs Ac
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요