GitHub
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作者による説明(英語の原文)
Cross-agent handoff: the next coding agent starts from the last one's facts, not a blank page.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
REMEMBRA_API_KEY, REMEMBRA_URL, REMEMBRA_AGENT_ID「秘密」と表示された値は、あなたのアカウントの鍵です。絶対に人に教えたり、チャットに貼り付けたりしないでください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"remembra": {
"command": "uvx",
"args": [
"remembra-mcp"
],
"env": {
"REMEMBRA_API_KEY": "your-value",
"REMEMBRA_URL": "your-value",
"REMEMBRA_AGENT_ID": "your-value"
}
}
}
}ターミナルでこれを実行します
claude mcp add remembra --env REMEMBRA_API_KEY=your-value --env REMEMBRA_URL=your-value --env REMEMBRA_AGENT_ID=your-value -- uvx remembra-mcp動かす前に、空欄の値を入力してください。
プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"remembra": {
"command": "uvx",
"args": [
"remembra-mcp"
],
"env": {
"REMEMBRA_API_KEY": "your-value",
"REMEMBRA_URL": "your-value",
"REMEMBRA_AGENT_ID": "your-value"
}
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"remembra": {
"type": "stdio",
"command": "uvx",
"args": [
"remembra-mcp"
],
"env": {
"REMEMBRA_API_KEY": "your-value",
"REMEMBRA_URL": "your-value",
"REMEMBRA_AGENT_ID": "your-value"
}
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
REMEMBRA_AGENT_ID envこの設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント remembra-ai で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
入力が必要なもの:REMEMBRA_API_KEY, REMEMBRA_URL
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.17.5)がレジストリに届いたのは13 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにPython (uv)も必要です。
同じカテゴリには:GitHub, Desktop Commander, Cloudflare MCP
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
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
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
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
冒頭だけを表示しています。続きはリポジトリで読めます