Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
作者提供的说明(英文原文)
Delegate a self-contained task to opencode's free-tier models as a one-shot subagent.
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。
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 …”。
链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。
在终端中运行这条命令
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。
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。
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 jayden99236 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(0.1.1)于2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 MCPB。
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。
Delegate a self-contained task to opencode as a one-shot subagent, from any coding agent (or human) that can run a shell command — or, more directly, straight from inside an AI chat client via MCP.
Listed on the official MCP Registry as io.github.jayden99236/consult-opencode, with a one-click .mcpb bundle attached to each release for Claude Desktop and other MCPB-compatible clients.
If you're driving an expensive/primary coding agent (Claude, GPT, etc.) through a session, it's often wasteful to spend one of its own turns on something small and self-contained: summarizing a file, drafting a regex, writing a boilerplate test, getting a second opinion. opencode ships its own free-tier models under the opencode/ provider namespace — zero config, no API key required. This repo gives you two ways to reach it:
mcp-server.mjs) — the easiest path. Add it once to your AI chat client's config and the model gets a native consult_opencode tool, no shell commands involved. See Direct integration below.consult-opencode.mjs) — zero dependencies, for agents/scripts that can only run shell commands, or for calling it yourself from a terminal.Both wrap the same core logic in lib.mjs.
npm install -g opencode-ai
The CLI script itself (consult-opencode.mjs + lib.mjs) has no dependencies beyond Node built-ins. The MCP server additionally needs @modelcontextprotocol/sdk and zod — run npm install in this repo to get those (see below).
MCP is the standard way to give an AI chat client a native tool without it having to shell out to anything. Once configured, the model just sees a consult_opencode tool it can call directly.
git clone https://github.com/jayden99236/consult-opencode.git
cd consult-opencode npm install
Add to your claude_desktop_config.json (find it here):
{
"mcpServers": { "consult-opencode": { "command": "node", "args": ["/absolute/path/to/consult-opencode/mcp-server.mjs"] } } }
Restart Claude Desktop and consult_opencode shows up as an available tool.
claude mcp add consult-opencode -- node /absolute/path/to/consult-opencode/mcp-server.mjs
Or add it to a project's .mcp.json directly using the same mcpServers block shown above.
Any MCP-compatible client takes the same shape: a command (node) and args (the absolute path to mcp-server.mjs), configured as a stdio server. Check your client's docs for where that config lives — the mcpServers entry above is portable as-is.
The tool takes task (required) and an optional model (defaults to opencode/big-pickle, opencode's free tier), and returns the subagent's response as text.
node consult-opencode.mjs "Summarize what this function does: ..."
Or install it globally to get a consult-opencode command:
npm install -g .
consult-opencode "Write a regex for US zip codes"
Pipe a task in instead of passing it as an argument:
cat some-file.js | consult-opencode "Explain what this file does"
| Flag | Description |
|---|---|
--model | Model to use (default: opencode/big-pickle, opencode's free tier). Once you've authenticated another provider in opencode (opencode providers login), you can point this at it, e.g. --model anthropic/claude-haiku-4-5. |
--json | Print { model, text, cost } as JSON instead of plain text. |
-h, --help | Show usage. |
Most coding agents can just run this as a shell command and read its stdout:
node /path/to/consult-opencode.mjs "task description here"
Exit code is non-zero on failure, with the error on stderr; stdout carries only the result text (or the JSON blob with --json), so it composes cleanly in scripts and pipelines.
opencode's compiled Windows binary (opencode.exe) has been observed to hang indefinitely when its stdout is an anonymous pipe — which is exactly what Node's child_process gives you by default when you capture a child process's output. This reproduced consistently (6/6 runs) across both a direct .exe spawn and a shell-wrapped one.
The fix: redirect the child's stdout/stderr to a real temp file on disk, then read the file back once the process exits, instead of piping. This works reliably on Windows and is harmless on other platforms, so consult-opencode always does it this way regardless of OS.
If you're integrating with opencode from your own Node tooling and see a hang with zero output, this is almost certainly why.
MIT