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)
Debug webhooks from your AI agent: inspect and replay captured webhooks on localhost.
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 …”。
适用于网页版、桌面版和手机版 Claude:
https://mcp.pipehero.app/mcp在终端中运行这条命令
claude mcp add --transport http pipehero https://mcp.pipehero.app/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"pipehero": {
"url": "https://mcp.pipehero.app/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": {
"pipehero": {
"type": "http",
"url": "https://mcp.pipehero.app/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。
ChatGPT 只能连接互联网上的服务器:
https://mcp.pipehero.app/mcp菜单名称可能因套餐和版本不同而略有差异。
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。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
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 pipehero 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
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
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。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(0.1.0)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。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Spec Driven Development, Remote Desktop Commander, dotnet-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.
MCP server for .NET symbols, XAML, source generators, and restricted workspace edit
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。
Pipehero tunnels your localhost to a public URL and captures every webhook, so you can inspect, replay, and debug them — including from your AI agent via MCP.
This repo is auto-published from Pipehero's source. It holds the public MCP manifest
and the agent skill. Issues/PRs welcome.
Let an agent (Claude Code, Cursor, Copilot, Windsurf, Zed, …) list your tunnels, read captured webhooks, and replay them to localhost.
claude mcp add --transport http pipehero https://mcp.pipehero.app/mcp
Your client opens the browser to sign in and approve — no token to paste.
For CI/headless, pass a token from https://pipehero.app/dashboard/settings:
claude mcp add --transport http pipehero https://mcp.pipehero.app/mcp \
--header "Authorization: Bearer "
curl -fsSL https://pipehero.app/install | sh
pipehero login claude mcp add pipehero -- pipehero mcp
Any MCP client works — add it to .cursor/mcp.json, claude_desktop_config.json, etc.:
{ "mcpServers": { "pipehero": { "command": "pipehero", "args": ["mcp"] } } }
| Tool | What it does |
|---|---|
list_tunnels | Your tunnels and whether each is online. |
list_requests(subdomain) | Recent captured webhooks for a tunnel. |
get_request(subdomain, id) | Full request + response (headers + body). |
replay_request(subdomain, id) | Replay a webhook to your localhost. |
start_tunnel(name, port) | Expose a local port on a public URL (local MCP only). |
stop_tunnel(name) | Stop a tunnel started with start_tunnel (local MCP only). |
list_api_collections, get_api_collection(collection_id) | Your saved API docs: folders, endpoints, environments (remote MCP, and local from 0.1.14). |
get_api_endpoint(collection_id, method + path) | One endpoint in full, with its version and response examples. |
upsert_api_endpoint(collection_id, method, path, …) | Create or update an endpoint by route, so docs follow your code. |
add_api_example(collection_id, method + path, name, status, …) | Save a response example. |
delete_api_endpoint(collection_id, method + path) | Remove an endpoint whose route is gone. |
import_api_spec(format, content) / export_api_collection(collection_id) | OpenAPI, Postman and curl, both ways. |
run_api_endpoint(collection_id, method + path, environment) | Send it and read the real response. |
save_captured_request(collection_id, tunnel, request_id) | Turn a real captured request into docs, without credentials. |
check_api_drift(collection_id, tunnel) | Compare the docs with real traffic (Pro/Team). |
list_api_monitors(collection_id) | Which endpoints are monitored and which are failing, with the last error (Pro/Team). |
list_api_proposals | What happened to your proposed changes, on workspaces that review AI changes. |
get_api_share_link(collection_id, method + path) | The endpoint's shareable link: a read-only page with its docs, examples and latest run. |
share_api_endpoint(collection_id, method + path, …) | Create that link (workspace-only by default), open it to anyone with the link, or invite people by email. |
share_api_collection(collection_id, …) | The same for a whole collection: every endpoint, read-only, never its environments. |
Because your agent has both the captured webhook and your codebase, it can explain *why* a handler failed — then fix it and replay to confirm.
Install the skill so your agent knows *when and how* to use Pipehero:
pipehero skill install
or copy SKILL.md into ~/.claude/skills/pipehero/SKILL.md.
MIT