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 gut check before risky agent actions: calibrated safe/intended probabilities, no API calls.
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。
GUTSY_URL, GUTSY_INFERENCE_DIR, GUTSY_PROCEED_MIN, GUTSY_BLOCK_MIN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": {
"gutsy": {
"command": "uvx",
"args": [
"gutsy-mcp"
],
"env": {
"GUTSY_URL": "your-value",
"GUTSY_INFERENCE_DIR": "your-value",
"GUTSY_PROCEED_MIN": "your-value",
"GUTSY_BLOCK_MIN": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add gutsy --env GUTSY_URL=your-value --env GUTSY_INFERENCE_DIR=your-value --env GUTSY_PROCEED_MIN=your-value --env GUTSY_BLOCK_MIN=your-value -- uvx gutsy-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": {
"gutsy": {
"command": "uvx",
"args": [
"gutsy-mcp"
],
"env": {
"GUTSY_URL": "your-value",
"GUTSY_INFERENCE_DIR": "your-value",
"GUTSY_PROCEED_MIN": "your-value",
"GUTSY_BLOCK_MIN": "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": {
"gutsy": {
"type": "stdio",
"command": "uvx",
"args": [
"gutsy-mcp"
],
"env": {
"GUTSY_URL": "your-value",
"GUTSY_INFERENCE_DIR": "your-value",
"GUTSY_PROCEED_MIN": "your-value",
"GUTSY_BLOCK_MIN": "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。
GUTSY_URL envGUTSY_INFERENCE_DIR envGUTSY_PROCEED_MIN envGUTSY_BLOCK_MIN 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8日
注册名称已通过 GitHub 账户 kouhxp 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(0.1.2)于31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 Python (uv)。
同一分类中有:Spec Driven Development, Remote Desktop Commander, NexusWindows
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.
Windows computer use in the background: desktop apps driven without your mouse or keyboard.
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。
A local gut check for coding agents. Before Claude Code, Codex, Cursor or Copilot runs rm -rf, force-pushes, deploys or sends something, it calls gut_check and gets back calibrated probabilities that the action is intended and safe, plus a recommendation: proceed, confirm (ask the user first) or block.
Runs on your CPU with gutsy (0.8B, 775 MB GGUF). No API calls, no per-call cost, deterministic, and your code never leaves the machine.
It's a fast second opinion that adds friction where it's warranted. It is not a security boundary: the agent decides whether to call it and writes the context it sees, and a 0.8B model is weak at ambiguity and multi-step rules (see the model card). Keep your normal permission settings on. Default thresholds aren't tuned for your workflow; log the probabilities and adjust them.
git clone https://github.com/kouhxp/gutsy
pip install -e gutsy/gutsy-inference hf download kouhxp/gutsy --include "gutsy-0.8b-v04*" --local-dir gutsy/gutsy-inference/models cd gutsy/gutsy-inference && cp models.example.json models.json gutsy-inference check && gutsy-inference serve # http://127.0.0.1:8765
Or set GUTSY_INFERENCE_DIR=/path/to/gutsy/gutsy-inference and gutsy-mcp starts it on first use.
Claude Code:
claude mcp add gutsy -- uvx gutsy-mcp
Cursor (.cursor/mcp.json) / Claude Desktop:
{ "mcpServers": { "gutsy": { "command": "uvx", "args": ["gutsy-mcp"] } } }
VS Code (.vscode/mcp.json):
{ "servers": { "gutsy": { "type": "stdio", "command": "uvx", "args": ["gutsy-mcp"] } } }
Codex (~/.codex/config.toml):
[mcp_servers.gutsy]
command = "uvx" args = ["gutsy-mcp"]
Then tell the agent when to use it (CLAUDE.md, AGENTS.md, .cursor/rules):
Before deleting files, rewriting git history, force-pushing, touching databases,
deploying, publishing or sending anything, call
gut_check. If it doesn't return
proceed, stop and ask me.
An MCP tool only runs if the agent remembers to call it. The hook runs on every risky-looking Bash command regardless. It can only ask or deny, never auto-approve.
uv tool install gutsy-mcp # puts gutsy-hook on PATH
.claude/settings.json:
{
"hooks": { "PreToolUse": [ { "matcher": "Bash", "hooks": [{ "type": "command", "command": "gutsy-hook", "timeout": 60 }] } ] } }
block becomes a confirmation prompt by default; set GUTSY_HOOK_ALLOW_DENY=1 to deny outright.
gut_check(action, context="", user_request="") returns:
{
"recommendation": "confirm", "reason": "Not confident enough to proceed without the user.", "p_intended": 0.41, "p_reversible": 0.08, "verdict_probabilities": {"proceed": 0.22, "confirm": 0.61, "block": 0.17}, "reject": 0.04, "confidence": 0.42 }
| env var | default | |
|---|---|---|
GUTSY_URL | http://127.0.0.1:8765 | runtime URL |
GUTSY_INFERENCE_DIR | lets gutsy-mcp start the runtime | |
GUTSY_MODEL | runtime default | model name from models.json |
GUTSY_PROCEED_MIN | 0.85 | |
GUTSY_BLOCK_MIN | 0.50 | |
GUTSY_API_KEY | if you run serve --api-key-env |
License: Apache 2.0.