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)
Typed noul / choice / score judgments from a local Laya model, with token-budget preflight.
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": {
"laya": {
"command": "npx",
"args": [
"-y",
"laya-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add laya -- npx -y laya-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"laya": {
"command": "npx",
"args": [
"-y",
"laya-mcp"
]
}
}
}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": {
"laya": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"laya-mcp"
]
}
}
}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 PerryLink 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(0.1.5)于上个月进入注册中心。
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, Tools 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.
Web production tools for AI agents: contrast, JP text, WebP, JSON-LD, slugs, dates and 40+ more
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。
MCP server for Laya typed decisions — noul (yes/no), choice, score — wrapped so it survives contact with a server.
English · 简体中文 · Español · Português · हिन्दी
npx -y laya-mcp --help
Registered as io.github.PerryLink/laya-mcp in the official MCP Registry.
This npm package is a launcher, not an implementation. Laya is a PyTorch
model, so the server itself is Python. Installing this package gets you the
Node entry point and nothing else; you also need the Python side:
`bash
pip install "laya-mcp[mcp]"
`
npx laya-mcpfinds that interpreter, hands stdio to it, and passes the MCP
stream through untouched. It does not install anything for you — fetching torch
(~2 GB) and a checkpoint (~650 MB) as a side effect of running a command is not
something a launcher should do.
On Windows, python on PATH is often the Microsoft Store execution alias, which is a stub: it cannot import anything, and it sits ahead of your real interpreter. The launcher therefore reports what it tried rather than claiming the package is missing. Point it at the right interpreter either way:
# name it outright
set LAYA_MCP_PYTHON=C:\path\to\python.exe # Windows export LAYA_MCP_PYTHON=/path/to/python # macOS, Linux
LAYACORE_PYTHONis still read. 0.1.0 and 0.1.1 printed that name in the error
message, and a launcher that stopped honouring the variable its own previous
version told you to set would be worse than one carrying the alias.
Status: 0.1.5, work in progress. The Python core is implemented and covered
by CI. The launcher itself is covered by ten checks over interpreter discovery,
which is where it has been wrong before. Interfaces may move before 1.0.
Laya truncates things silently and reports none of it:
This package adds a preflight that reports what would be cut, structured errors that name the offending question, an honest confidence contract, and a health surface that admits a demotion.
laya-mcp serve # warm HTTP sidecar on 127.0.0.1:8787 (loads the model once)
laya-mcp mcp # MCP over stdio laya-mcp doctor # what is installed, and whether the GPU really works laya-mcp install # register with whichever agent harness you have
install handles the fact that there is no portable way to register an MCP server: Claude Code (mcpServers), Codex ([mcp_servers. ]), opencode (mcp, with an array command), OpenClaw (mcp.servers) and Hermes (mcp_servers) each get the right shape written to the right file, merged and backed up rather than overwritten. pi has no native MCP support and is reported as unsupported.
Prefer serve plus --sidecar over hosting the model in each stdio process: a harness spawns one server per session, and loading a 650 MB checkpoint per session is the main reason a Python-backed MCP server feels slow.
Upstream's own numbers, repeated because an integration that implies otherwise is lying to you: the base checkpoints are near chance zero-shot on typed decisions (0.362 against a 0.461 majority-class baseline); score is the weakest primitive (35% vs 70% in independent measurement); raw calibration error is 0.466 before temperature fitting; and one fixture run answered "A" on 46 of 50 multiple-choice items.
Calibration makes a probability honest; it cannot make a model right.
Apache-2.0. Laya is Apache-2.0 by Convai Innovations. This is an independent integration, not affiliated with or endorsed by that project.