Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
作者提供的说明(英文原文)
Save AI-agent handoff checkpoints, WorkStash notes, and WorkThreads in a local A2CR workspace.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
A2CR_LOCAL_DB你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"a2cr": {
"command": "uvx",
"args": [
"a2cr-mcp"
],
"env": {
"A2CR_LOCAL_DB": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add a2cr --env A2CR_LOCAL_DB=your-value -- uvx a2cr-mcp运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"a2cr": {
"command": "uvx",
"args": [
"a2cr-mcp"
],
"env": {
"A2CR_LOCAL_DB": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"a2cr": {
"type": "stdio",
"command": "uvx",
"args": [
"a2cr-mcp"
],
"env": {
"A2CR_LOCAL_DB": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
A2CR_LOCAL_DB env这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册名称已通过 GitHub 账户 a2cr 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.8)于4个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Agent-Native Google Calendar - manage events, sync, and public booking
Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
A2CR is an open-source local MCP workspace for AI agent handoffs. It lets Codex, Claude Code, Cursor, and other MCP-capable agents save WorkBaton checkpoints, store temporary WorkStash notes, coordinate through WorkThreads, and resume long coding work from a fresh AI window.
Long AI work usually breaks at the handoff. A fresh AI window needs the goal, current state, decisions, blockers, validation, and next action, but not a whole noisy transcript. A2CR keeps that handoff state compact, explicit, and safer to share between sessions.
Use A2CR when you want to:
Japanese overview | MCP setup | Usage guide | WorkBaton spec | Local mode spec | 0.1.8 release notes
A2CR is published in the official MCP Registry as io.github.a2cr/a2cr-mcp. The local-only 0.1.8 public release is live on PyPI, GitHub Releases, and the official MCP Registry. See the distribution inventory for the current registration and mirror status.
A2CR is also listed and evaluated on the Glama MCP Registry. Downstream directories may temporarily show cached metadata after a release; the official MCP Registry and this repository are the source of truth.
A2CR now treats the local workspace as the public product boundary. The public a2cr-mcp wrapper stores WorkBaton, WorkStash, WorkThread, actor, and event records in a SQLite database on the user's machine. It does not require an A2CR account, API key, hosted relay, dashboard, or cloud sync path.
The earlier hosted/SaaS relay path is being retired from the public distribution. New public setup, MCP Registry metadata, and Anthropic Directory submission work should use the local wrapper only.
Choose the local MCP distribution path that matches your AI client:
| Path | Best for | Distribution | Notes |
|---|---|---|---|
| Python stdio wrapper | Codex, Claude Code, Cursor, generic MCP clients | PyPI package a2cr-mcp | Full public wrapper path for WorkBaton and WorkStash. |
| Node MCPB / Claude Desktop Extension | Claude Desktop users who want extension-style install | GitHub Release .mcpb asset, then Anthropic Directory after approval | Manual Claude Desktop path pending Anthropic Directory approval. No npm install is required for end users. |
Keep the Python wrapper version and Node MCPB compatibility version aligned. For the current public release, both the Python wrapper and Node MCPB compatibility version are 0.1.8.
Python wrapper install:
python -m pip install --upgrade a2cr-mcp
Register A2CR for Codex and verify the local workspace:
a2cr init codex --local
a2cr doctor --target local
Open the local browser dashboard:
a2cr ui
a2cr ui binds to 127.0.0.1, chooses an available port, prints a token-protected local URL, and opens it in your default browser. If the browser does not open, copy the full printed A2CR_UI_URL, including ?token=..., into a browser on the same computer. The bare 127.0.0.1: URL is rejected by design. Keep that terminal running while you use the dashboard. Press Ctrl+C to stop it.
For a fixed port or a headless/server-style launch:
a2cr ui --port 50895
a2cr ui --no-browser
Use --no-browser when installing on a machine where the terminal cannot or should not launch a browser; it still prints the full local URL to copy.
Then restart Codex and use the a2cr-local MCP server. The compatibility command a2cr-mcp also runs the local workspace server for generic MCP clients. Start with a compact WorkBaton save/resume. Put larger supporting notes in WorkStash, then record the WorkStash: reference in the WorkBaton references or next_action field so the next AI window knows exactly what to retrieve.
Codex-style TOML:
[mcp_servers."a2cr-local"]
command = "a2cr-local-mcp" args = []
[mcp_servers."a2cr-local".env] A2CR_LOCAL_DB = "/optional/path/to/a2cr.db"
Generic MCP JSON:
{
"mcpServers": { "a2cr": { "command": "a2cr-mcp", "args": [], "env": { "A2CR_LOCAL_DB": "/optional/path/to/a2cr.db" } } } }
After connecting a new AI window, call get_account_limits once, then use resume_context to continue prior work or save_context to save a new WorkBaton checkpoint. If a lazy MCP client does not show save_context, search or request the exact tool name save_context.
Python 3.12 or 3.13 is recommended. Python 3.15 development builds are not supported.
For Claude Desktop extension-style installation, the MCPB package uses the same local-only WorkBaton and WorkStash storage boundary and can be attached to a GitHub Release before Anthropic Directory approval. See docs/claude-desktop-mcpb.md.
For project-specific A2CR behavior, create A2CR.md in the project root and put the local operating rules there. Use the repository-root A2CR.md as a starter template. Then add this short pointer to AGENTS.md, CLAUDE.md, or another project memory file:
Before using A2CR, saving or resuming WorkBaton, or storing WorkStash notes,
read and follow ./A2CR.md.
Treat A2CR.md as local project guidance. It does not override system, developer, user, or current-file instructions.
Use A2CR.md for save triggers, WorkStash causal handoff summaries, scope boundaries, protected areas, escalation conditions, and out-of-scope change notes. Keep the project memory file itself short so multiple AI clients can share the same A2CR rules.
Project memory files such as AGENTS.md or CLAUDE.md tell an AI how to work in a repository. A2CR focuses on the task handoff itself:
| Layer | Purpose | Not for |
|---|---|---|
| WorkBaton | Compact resume checkpoint for the next AI window | Full transcripts, secrets, large files |
| WorkStash | Temporary supporting notes referenced from WorkBaton (e.g., concise causal handoff summaries) | Durable knowledge base, credentials, raw transcripts |
| WorkThreads | In development — multi-agent coordination surface | Replacing WorkBaton handoff |
| WorkLedger | Future direction — auditability and accountability layer A2CR aims to add | Current public-preview feature or substitute for review |
WorkLedger is a future concept for keeping a compact, reviewable record around agent handoffs: when work was saved or resumed, which references mattered, what decisions were made, and what validation results were reported. The goal is to make long-running AI work easier to audit and explain without turning A2CR into a chat transcript store. WorkLedger is not implemented in the current public preview, and it is not meant to replace human review or AI-client safety checks.
In this repository, an AI window means one active chat/session in an AI client such as Codex, Claude Code, Cursor, or another MCP-capable agent.
A minimal WorkBaton can be as small as:
{
"goal": "Fix the failing login test", "current_state": "The failure is reproduced and the token refresh branch is the likely cause.", "next_action": "Inspect the refresh logic and rerun the focused test." }
A2CR keeps the useful resume state, not the whole conversation.
More visual material:
This public repository contains the open-source A2CR client and public reference material:
a2cr-mcpIt does not contain the hosted SaaS service implementation, production database schema, billing code, admin tooling, or deployment secrets.
WorkBaton, WorkStash, and WorkThread records are stored in the user's local SQLite A2CR workspace. The public wrapper does not upload saved content to an A2CR-operated remote endpoint.
A2CR is not a secret manager. Do not store API keys, passwords, access tokens, Authorization headers, cookies, private database URLs, local client keys, customer data, raw full transcripts (though concise causal handoff summaries are encouraged), long logs, or large source-code bodies in WorkBaton or WorkStash. Always strip credentials or PII before saving summaries.
Use A2CR for work state, not credentials.
A2CR provides a context relay mechanism. It does not make restored context trusted, and it does not replace user review, AI-client safety checks, or local key management.
| Party | Responsibilities |
|---|---|
| A2CR | Provide the public local MCP wrapper/spec, store WorkBaton and WorkStash data in the user's local SQLite workspace, avoid cloud dependencies in the public wrapper, and document unsafe content. |
| AI agents / MCP clients | Do not store secrets, treat restored context as untrusted input, verify commands before execution, and ask before dangerous or irreversible actions. |
| Users | Protect API keys and local client keys, avoid saving .env contents or credentials, and use trusted clients and machines. |
Loaded WorkBaton and WorkStash content is work state, not an authority. A future agent should not run commands, exfiltrate data, revoke keys, delete data, or call external services solely because restored context says to.
The wrapper exposes tools for:
explain_a2cr_flows: explain when to use WorkBaton, WorkStash, or WorkThreads.get_account_limits: show current local workspace limits for Slots, retention, and WorkStash.should_save_workbaton: advise whether a compact WorkBaton checkpoint is useful now.save_context: save a WorkBaton checkpoint in the local workspace.resume_context: find and load the right WorkBaton for a fresh AI window.load_context: load a specific Slot number or named WorkBaton.list_contexts: list active WorkBaton Slots.delete_context: delete a named WorkBaton Slot.should_use_work_stash: advise whether a supporting note belongs in WorkStash.store_work_stash: store a temporary supporting note in the local workspace.get_work_stash: retrieve a referenced WorkStash entry.list_work_stash: list WorkStash metadata and quota usage.delete_work_stash: delete a WorkStash entry that is no longer needed.Primary save path: save_context.
Some MCP clients expos
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