Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add plhys/Cloud2Local --skill cloud-to-localgit clone --depth 1 https://github.com/plhys/Cloud2LocalWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/plhys/cloud2local/cloud-to-local)<a href="https://agentmods.dev/skills/plhys/cloud2local/cloud-to-local"><img src="https://agentmods.dev/badge/skills/plhys/cloud2local/cloud-to-local/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/plhys/cloud2local/cloud-to-local"><img src="https://agentmods.dev/badge/skills/plhys/cloud2local/cloud-to-local.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00046 | $0.01402 |
| Opus 5.5 | $0.00018 | $0.00561 |
| Sonnet 5.5 | $0.00009 | $0.00280 |
| Haiku 4.5 | $0.00005 | $0.00140 |
Grade A, and why
cloud2local scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s http://127.0.0.1:8000/health How it starts
The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cloud2Local 云端 MCP 接入
把本机 Cloud2Local 的 MCP Server 暴露给云端智能体:云端填公网 URL + Token 即可操作本机(受 fileRoot / 命令白名单约束)。
职责边界(别写歪)
- Skill 只负责「怎么连上」:公网 URL、Token/headers、端口、暴露状态、排障、安全边界。
- Skill 不负责「能干嘛」的工具清单:连上 MCP 后,客户端会走协议的
list_tools自动发现工具与参数。 - 不要在 Skill 里维护长篇 tools 目录(会过期、和协议重复)。最多一句话说明用途。
- 本机已在跑的 Agent 不需要再绕这个 MCP;这套给云端/远程 Agent 用。
关键:两个端口别混
| 名称 | 默认 | 谁用 | 说明 |
|---|---|---|---|
本机端口 localPort |
8000 |
本机 MCP | 本机监听;云端不要直连 |
公网端口 remotePort |
18000 |
云端智能体 | 公网入口;服务器必须放行 |
映射:
云端 http://PUBLIC_HOST:18000/mcp --> 本机 127.0.0.1:8000/mcp
何时使用
- 用户要让云端 Agent / WorkBuddy / Cursor 连本机 MCP(Cloud2Local)
- 用户问云端 MCP URL、Token、headers 怎么填
- 用户说「MCP 本机能用,云端连不上」
- 用户问该用 8000 还是 18000
前置条件
- 本机 Cloud2Local 外网通道已就绪(应用首页已连接)
- MCP 页 Server 已启动(本机 8000 有服务)
- MCP 页暴露状态显示 已就绪
- 云端地址端口是 公网端口(默认 18000),不是本机 8000
- 已设置 Token(云端强烈建议)
接入地址规则
本机:
http://127.0.0.1:<localPort>/mcp
云端(优先):
http://<publicHost>:<remotePort>/mcp
旧客户端:
http://<publicHost>:<remotePort>/sse
字段来源:
| 字段 | 来源 |
|---|---|
| localPort | MCP「本机端口」,默认 8000 |
| remotePort | MCP「公网端口」,默认 18000;0 才表示等于 localPort |
| publicHost | MCP「公网主机」;空则用应用配置页的服务器地址 |
| proxy name | 自动代理固定名 mcp-auto-expose |
Token / Header
有 Token 时,请求必须带头之一:
Authorization: Bearer <token>
或:
X-MCP-Token: <token>
也兼容 query:?token=<token>(不推荐,易泄露)。
云端客户端配置模板
{
"mcpServers": {
"cloud2local": {
"url": "http://PUBLIC_HOST:18000/mcp",
"headers": {
"Authorization": "Bearer YOUR_TOKEN"
}
}
}
}
WorkBuddy 自定义 MCP(~/.workbuddy/mcp.json)常见形态同上(key 名可自定,核心是 url + headers)。
若客户端只认 SSE,把路径改成 /sse 即可。
详细模板见 references/client-configs.md。
本机侧标准操作
- 打开 Cloud2Local,确认外网通道在线
- MCP 页设置:
- 自动公网暴露:开
- 本机端口:8000(本机用)
- 公网端口:18000(云端用)
- 公网主机:有域名就填;否则留空
- Token:必填(云端)
- fileRoot / 允许命令:尽量收紧
- 保存配置 → 启动 Server
- 确认状态:
- Server 运行中
- 公网暴露 = 已就绪
- 云端地址端口是 18000(不是 8000)
- 点「复制云端客户端配置」给云端使用
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 165 lines · 46 tokens per session scan A 7ce742773f8e
cloud2local is a skill published in the GitHub repository plhys/Cloud2Local (0 stars, last pushed 3mo ago), licensed MIT. It adds 46 tokens to every session and 1,402 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
cloud2local compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| cloud2localplhys/Cloud2Local | Skill | 0 | 3mo ago | MIT | A | 46 | Claude Code, Codex |
| gke-compute-classesgoogle/skills | Skill | 24k | 2d ago | Apache-2.0 | A | 83 | Claude Code, Codex |
| gke-workload-securitygoogle/skills | Skill | 24k | 2d ago | Apache-2.0 | A | 171 | Claude Code, Codex |
| gke-reliabilitygoogle/skills | Skill | 24k | 2d ago | Apache-2.0 | A | 85 | Claude Code, Codex |
| cloud-architectJeffallan/claude-skills | Skill | 12k | 9d ago | MIT | A | 71 | Claude Code |
| nemo-automodel-launcher-configNVIDIA/skills | Skill | 3.9k | 2d ago | Apache-2.0 | A | 30 | Claude Code |
| azure-mgmt-botservice-dotnetmicrosoft/skills | Skill | 3.2k | 2d ago | MIT | A | 78 | Claude Code |