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otgate — OT policy gateway

作者:alikup-ai版本 0.1.1i★ –i在你的电脑上运行
注册名称io.github.alikup-ai/otgate-opcua

安装

概览

作者提供的说明(英文原文)

Gates an LLM agent's writes to an OPC UA server on ranges, rate of change and live interlocks.

PopNx MCP 的三大支柱

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。

它能帮你做什么

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。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: OTGATE_BACKEND, OTGATE_POLICY, OTGATE_AUDIT, OTGATE_SHADOW, OTGATE_RATE_HISTORY, OTGATE_OPCUA_ENDPOINT

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

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": {
    "otgate-opcua": {
      "command": "uvx",
      "args": [
        "otgate"
      ],
      "env": {
        "OTGATE_BACKEND": "your-value",
        "OTGATE_POLICY": "your-value",
        "OTGATE_AUDIT": "your-value",
        "OTGATE_SHADOW": "your-value",
        "OTGATE_RATE_HISTORY": "your-value",
        "OTGATE_OPCUA_ENDPOINT": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add otgate-opcua --env OTGATE_BACKEND=your-value --env OTGATE_POLICY=your-value --env OTGATE_AUDIT=your-value --env OTGATE_SHADOW=your-value --env OTGATE_RATE_HISTORY=your-value --env OTGATE_OPCUA_ENDPOINT=your-value -- uvx otgate

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "otgate-opcua": {
      "command": "uvx",
      "args": [
        "otgate"
      ],
      "env": {
        "OTGATE_BACKEND": "your-value",
        "OTGATE_POLICY": "your-value",
        "OTGATE_AUDIT": "your-value",
        "OTGATE_SHADOW": "your-value",
        "OTGATE_RATE_HISTORY": "your-value",
        "OTGATE_OPCUA_ENDPOINT": "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。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "otgate-opcua": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "otgate"
      ],
      "env": {
        "OTGATE_BACKEND": "your-value",
        "OTGATE_POLICY": "your-value",
        "OTGATE_AUDIT": "your-value",
        "OTGATE_SHADOW": "your-value",
        "OTGATE_RATE_HISTORY": "your-value",
        "OTGATE_OPCUA_ENDPOINT": "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。

需要你填写的值

  • OTGATE_BACKEND env
    Backend to gate: 'fake' for the bundled in-memory reactor simulator, 'asyncua' for a real OPC UA server. Start with 'fake' — it needs no plant and no extra dependency.
  • OTGATE_POLICY env
    Path to the policy YAML. Any tag not listed in it is denied by default.
  • OTGATE_AUDIT env
    Path to the append-only JSONL audit log. Every call, allowed or not, produces exactly one line.
  • OTGATE_SHADOW env
    Set to 1 to run in shadow mode: allowed writes are recorded as 'WOULD execute' and never reach the backend. Use this to watch an agent for a while before letting it touch anything.
  • OTGATE_RATE_HISTORY env
    Path to a JSONL file that keeps the rate-of-change time base across restarts. Without it a restart loses the time base, and rate limits fall back to a one-interval allowance.
  • OTGATE_OPCUA_ENDPOINT env
    OPC UA endpoint, e.g. opc.tcp://localhost:4840. Required when OTGATE_BACKEND=asyncua.

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。

它能做什么

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。

基础检查i

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

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 alikup-ai 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    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“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 5679 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 5679 个服务器的 98% 更新
  • 基础检查结果等于或优于此分类中其他 5679 个服务器的 100%

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。

常见问题

otgate — OT policy gateway 安全吗?

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。

它需要哪些密钥或代码?

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。

它在我的电脑上运行还是在云端?

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)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.1)于今天进入注册中心。

哪些应用可以使用它?

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)。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

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

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT昨天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT21天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT2个月前更新
安装

作者的 README

打开 README

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。

otgate

An OT-aware authorization gateway that sits between an LLM agent and an industrial OPC UA server, applying a process-aware access policy — value ranges, rate limits, interlocks — to every call the agent makes.

Русская версия →

[MCP client / agent] ---MCP---> [otgate] ---OPC UA---> [OPC UA server]

| [policy engine + audit + shadow mode]

The same decisions as terminal output ( python examples/demo.py )

otgate is itself an MCP server. The agent connects to it as if it were an ordinary OPC UA MCP; internally otgate holds a client to the real OPC UA server. Every call is transparent to the agent, and otgate intercepts each one to apply policy and record an audit line.

Why

  • Existing OPC UA MCP servers write to tags with no authorization layer — the agent has full, unbounded access.
  • Existing LLM guardrails (LlamaFirewall, NeMo Guardrails) work on text/prompts and do not understand process semantics — they know nothing about ranges, rates of change, or interlocks.
  • otgate closes exactly that gap: OT semantics + admission policy + audit.

It is not "you may write to this tag" but "you may write *within range X, no faster than Y over interval Z, and only while the emergency tag W is not active*".

Where this fits: OWASP ASI02

In the OWASP Top 10 for Agentic Applications, the risk otgate targets is ASI02 — Tool Misuse & Exploitation: an agent that stays inside its granted privileges but uses a legitimate tool unsafely — parameter pollution, excessive execution, or a call that is only dangerous given the current system state.

Identity and access layers (ASI03) answer *may this agent call this tool*. They do not look at what it writes, how fast, or under which conditions. otgate is the layer that does:

ASI02 sub-mechanismotgate
Parameter pollutionvalue_range — the argument itself is checked
Excessive execution / scalemax_rate over rate_interval, durable across restarts
Unsafe given system stateinterlocks — reads live guard tags before allowing
Unsafe composition (salami attack)cumulative_range — bounds total drift over a window, so slicing a forbidden move into legal steps does not work
Recursion / call stormsmax_calls over calls_interval
Unverifiable safety conditionfails closed — denies rather than guesses

Per-step limits judge one write; cumulative limits judge a *series*. Without the latter an agent walks around max_rate with many small legal steps:

step 1: 50.0 -> 52.5  (drift  +2.5)  ALLOW

step 2: 52.5 -> 55.0 (drift +5) ALLOW step 3: 55.0 -> 57.5 (drift +7.5) ALLOW step 4: 57.5 -> 60.0 (drift +10) ALLOW step 5: 60.0 -> 62.5 (drift +12.5) DENY cumulative drift too large: 62.5 is +12.5 from 50, allowed [-10, 10]

A full mapping against all ten OWASP agentic risks — including what otgate explicitly does not cover (tool-chain manipulation, goal hijacking, memory poisoning, rogue-agent detection) — is in [docs/threat-model.md](docs/threat-model.md).

Install

pip install -e .           # core: FakeBackend, engine, MCP server

pip install -e ".[dev]" # + pytest for the test suite pip install -e ".[opcua]" # + asyncua for a real OPC UA backend

Python 3.11+.

Policy example

A policy is a YAML list of per-tag rules. Any tag not listed is denied by default.

# examples/reactor_policy.yaml
  • tag: "ns=2;s=Reactor.TIC101.PV" # temperature, read-only access: read
  • tag: "ns=2;s=Reactor.TIC101.SP" # temperature setpoint access: write_with_approval # writes need human approval (ASK) value_range: [40, 80] # only within 40..80 degC cumulative_range: [-10, 10] # ... and no more than 10 degC total drift cumulative_interval: 3600 # from where it stood an hour ago max_rate: 5 # no faster than 5 degC ... rate_interval: 60 # ... per 60 seconds interlocks:
  • tag: "ns=2;s=Reactor.ESD" # blocked while emergency shutdown ... condition: "== true" # ... is active action: deny

Access levels: read, write, write_with_approval, deny.

Write check order (first failing check wins): tag-in-policy → access → value range → interlocks → rate of change → approval → allow.

Demo

python examples/demo.py
otgate demo — agent interacting with a reactor via the policy gateway

read temperature (PV) ALLOW read allowed -> 55.0 write setpoint = 60 degC (in range) ASK write requires human approval write setpoint = 200 degC (out of range) DENY value 200.0 is outside allowed range [40.0, 80.0] write setpoint = 60 degC while ESD active DENY interlock active: ns=2;s=Reactor.ESD == True (current ns=2;s=Reactor.ESD = True) write setpoint = 78 degC one second later DENY rate of change too high: |78.0 - 50.0| = 28 in 1s exceeds 5 per 60s

audit log


{"timestamp": "...", "action": "read", "node_id": "ns=2;s=Reactor.TIC101.PV", "value": null, "decision": "ALLOW", "reason": "read allowed", "shadow": false, "executed": true} {"timestamp": "...", "action": "write", "node_id": "ns=2;s=Reactor.TIC101.SP", "value": 60.0, "decision": "ASK", "reason": "write requires human approval", "shadow": false, "executed": false} {"timestamp": "...", "action": "write", "node_id": "ns=2;s=Reactor.TIC101.SP", "value": 200.0, "decision": "DENY", "reason": "value 200.0 is outside allowed range [40.0, 80.0]", "shadow": false, "executed": false} {"timestamp": "...", "action": "write", "node_id": "ns=2;s=Reactor.TIC101.SP", "value": 60.0, "decision": "DENY", "reason": "interlock active: ns=2;s=Reactor.ESD == True (current ns=2;s=Reactor.ESD = True)", "shadow": false, "executed": false} {"timestamp": "...", "action": "write", "node_id": "ns=2;s=Reactor.TIC101.SP", "value": 78.0, "decision": "DENY", "reason": "rate of change too high: |78.0 - 50.0| = 28 in 1s exceeds 5 per 60s", "shadow": false, "executed": false}

Run as an MCP server

Published to the official MCP Registry as `io.github.alikup-ai/otgate-opcua`, and to PyPI as `otgate`.

The registry name carries opcua because its search matches on the server name only and does not index

descriptions, so a bare otgate is findable only by someone who already knows the word.

otgate exposes: read_tag, write_tag, browse, get_audit_log, and the operator approval tools list_pending, approve, deny.

otgate                      # console script (stdio transport)

python -m otgate.server # equivalent

Configuration is via environment variables (so the backend switches without code changes):

VariableDefaultMeaning
OTGATE_BACKENDfakefake or asyncua
OTGATE_POLICYexamples/reactor_policy.yamlpolicy YAML path
OTGATE_AUDITaudit.jsonlaudit log path
OTGATE_SHADOW*(off)*1/true to enable shadow mode
OTGATE_RATE_HISTORY*(in-memory)*path to a JSONL file to make rate-of-change history survive restarts
OTGATE_OPCUA_ENDPOINT—required when backend is asyncua
OTGATE_AGENT_TOKEN—bearer token for the single-agent HTTP channel
OTGATE_AGENTS—path to agents.yaml for multi-agent mode (overrides single-agent)
OTGATE_OPERATOR_TOKEN—bearer token for the operator HTTP channel (must differ from every agent token)
OTGATE_HOST / OTGATE_AGENT_PORT / OTGATE_OPERATOR_PORT127.0.0.1 / 8770 / 8771HTTP bind host and ports

Example MCP client config (FakeBackend):

{

"mcpServers": { "otgate": { "command": "otgate", "env": { "OTGATE_BACKEND": "fake" } } } }

Related work: the layer underneath

otgate governs what the process allows right now — ranges, rate against the live value, interlocks, drift, approval. It does not try to be the access layer underneath that, and there is a good one: IndustriAgents/OPCUA-MCP answers *may this caller touch this node at all* — read-only by default, control profiles, allowlisted targets, pinned certificates, audited control calls.

The two questions are genuinely different. A write of 40 °C to an allowlisted target satisfies every access rule and is still wrong if the tag reads 22 °C and the ramp violates a thermal limit. Access control without process limits permits that write; process limits without access control have nothing to stand on.

A visible difference in the audit trail shows the split: their acceptance criteria require records to carry profile, tool, decision and target IDs without values, which is right for an access log. otgate records the value, because "200.0 refused, outside [40, 80]" is not a sentence you can write without it.

Connecting a real OPC UA server

No code changes — install the extra and point the config at your server:

pip install -e ".[opcua]"

export OTGATE_BACKEND=asyncua export OTGATE_OPCUA_ENDPOINT=opc.tcp://localhost:4840 otgate

The backend lives behind an abstract interface (otgate/backends/base.py) with two implementations — FakeBackend (in-memory simulator, no dependencies) and AsyncuaBackend (real OPC UA). asyncua is imported lazily, so the fake backend, the tests and the demo run without it.

Shadow mode

With OTGATE_SHADOW=1, a write that the engine allows is not executed on the backend — instead the audit records a "WOULD execute" line with executed: false. This lets you run an agent and see what it *would* do to the process without any real effect.

Human approval workflow

A write_with_approval tag returns ASK. Rather than silently drop the write, otgate parks it as a pending request with a TTL and hands the agent an approval id. A human then resolves it through the operator tools:

  • list_pending — show parked write requests.
  • approve — approve and execute, *after re-checking policy* against the current process state. If an interlock tripped or the value drifted out of range while the request waited, the approval is recorded but the write is blocked — an approval is intent, never a blind execute.
  • deny — reject; the write never runs.

Requests

只显示了开头部分;其余内容请在仓库中阅读

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