Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Local MCP runtime for policy-governed, verified agent actions with durable receipts.
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": {
"melra": {
"command": "npx",
"args": [
"-y",
"@melra/cli",
"serve"
]
}
}
}在终端中运行这条命令
claude mcp add melra -- npx -y @melra/cli serve粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"melra": {
"command": "npx",
"args": [
"-y",
"@melra/cli",
"serve"
]
}
}
}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": {
"melra": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@melra/cli",
"serve"
]
}
}
}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7日
注册名称已通过 GitHub 账户 XAGI-Lab 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(0.3.0-alpha.14)于22天前进入注册中心。
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 Node.js。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Microsoft Exchange Online MCP
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Exchange Online admin for MSPs: forwarding audits, EWS posture and offboarding, no PowerShell
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。
Modular Execution Layer for Reliable Autonomy
An open-source local execution runtime for agent tool calls you route through MELRA. It checks each call against policy, requests approval when needed, verifies declared evidence, and keeps a redacted receipt of what runs to an outcome. For each task, MELRA dispatches mutations at most once; uncertain outcomes are parked for reconciliation instead of replay. Exactly-once external effects still depend on the provider. Calls made through other tools remain outside MELRA's control.
Works with
26-second demo · Quick start · How it works · See what it is doing · Docs · Contribute · Discussions · Product Hunt launch
https://github.com/user-attachments/assets/e5cf895d-7ea6-4797-a1ef-e69cc5860d3f
[!WARNING]
MELRA is alpha software. The local runtime is tested end to end, but APIs may
change before
1.0. Use an isolated workspace, keep domain and command allowlists
narrow, and read every approval before you give it.
You need Node.js 22.13 or newer, or 23.4 or newer. From the project the agent should work in, one command sets everything up:
cd ~/project
npx @melra/cli@alpha setup
That directory becomes the agent's workspace, the boundary for its file and command operations. setup shows it, and asks before making your home directory, a directory holding it, or / the workspace; set MELRA_WORKSPACE to choose another.
In a terminal, setup is a short wizard. It writes a safe local policy, finds the agent apps on your machine, asks which one should use MELRA, and writes MELRA into that app's own config file, keeping everything else in it (and saving a .bak first):
Which MCP client should use MELRA?
Choose 1-26 [1]: 1 Write it into ~/project/.mcp.json? [Y/n]
✓ Workspace ~/project ✓ Policy ~/.melra/policy.json ✓ Claude Code ~/project/.mcp.json
Next: Start claude in this workspace and approve the 'melra' server when it asks; 'claude mcp list' then shows it connected. Or start it with 'melra launch claude-code', so MELRA's are the only tools it has that change anything.
Then restart your agent app (Claude Code asks you to approve a project's server once) and ask it to do something, for example *"use melra to show me the system info"*. That's it.
Prefer flags, a container, or building from source?
| How | Command |
|---|---|
| One client, no questions | npx @melra/cli@alpha setup --client cursor --write |
| Print the config instead of writing it | npx @melra/cli@alpha setup --client codex |
| Install globally | npm install -g @melra/cli@alpha && melra setup |
| Container (no Node needed) | docker run --rm ghcr.io/xagi-lab/melra:alpha doctor |
| Prebuilt release | download from releases, verify against SHA256SUMS, then node melra/dist/bin.js doctor |
| From source | git clone https://github.com/XAGI-Lab/melra.git && cd melra && corepack enable && pnpm install --frozen-lockfile && pnpm build && pnpm melra setup |
| One file, no Node needed *(experimental)* | from a checkout: pnpm build:sea, then ./dist-sea/melra setup; see single executable |
| Check what you installed | npm audit signatures verifies registry signatures; npm provenance links each package to its GitHub Actions build (see npm packages) |
Every command prints readable output in a terminal and plain JSON when piped or with --json, so scripts keep working. MELRA creates /payload.key with private permissions on first start; back it up with the SQLite files, because losing it makes persisted payloads unreadable. See installation for every install path, environment variable, and the hardened Docker invocation.
[!CAUTION]
This project publishes only under the
@melra/npm scope (@melra/cliis the CLI)
and on its releases, where the Python
SDK's wheel is. An unscoped npm package
melraor a PyPI packagemelrais
not this project's. Install from that scope, from this repository, or from the
releases.
If MELRA helps, star the repository so other agent builders can find it. Trying it in Cursor or another client? Share the client and its version, your OS, and your MELRA version (npx @melra/cli@alpha version) in issue #184; partial test results are useful too.
AI agents no longer just talk. They edit files, run commands, click through websites and call APIs on your behalf. Four questions come with that, and most agents answer them differently, or not at all:
Every action MELRA receives is checked against your policy, and checked again at the moment it runs. Risky changes wait for your exact approval.
"No error" is not success. An action counts only when the evidence you declared holds: the file exists, the exit code is 0, the page says what it should. For a file change or a memory delete MELRA also checks the end state itself: a written file holds exactly the bytes sent.
Every mutation MELRA dispatches is recorded before it runs and runs at most once. After a crash, MELRA settles it from its evidence or the provider; what it cannot settle waits in recovery_required and is never replayed.
Every action MELRA runs to an outcome leaves a redacted, append-only receipt and a certificate that carries its own digest, so you can audit what ran, who asked, and why it was allowed.
MELRA answers those questions in one place for tool calls routed through it, across supported agents. It sits underneath your agent for those calls, the way an operating system sits underneath your apps:
<img src="docs/assets/read
只显示了开头部分;其余内容请在仓库中阅读