Context7
Up-to-date docs for AI agents
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.
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。
OTGATE_BACKEND, OTGATE_POLICY, OTGATE_AUDIT, OTGATE_SHADOW, OTGATE_RATE_HISTORY, OTGATE_OPCUA_ENDPOINT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": {
"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。
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。
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。
OTGATE_BACKEND envOTGATE_POLICY envOTGATE_AUDIT envOTGATE_SHADOW envOTGATE_RATE_HISTORY envOTGATE_OPCUA_ENDPOINT 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 alikup-ai 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(0.1.1)于今天进入注册中心。
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:Context7, Codebase Memory, Exa
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
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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。
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.
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*".
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-mechanism | otgate |
|---|---|
| Parameter pollution | value_range — the argument itself is checked |
| Excessive execution / scale | max_rate over rate_interval, durable across restarts |
| Unsafe given system state | interlocks — 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 storms | max_calls over calls_interval |
| Unverifiable safety condition | fails 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).
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+.
A policy is a YAML list of per-tag rules. Any tag not listed is denied by default.
# examples/reactor_policy.yaml
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.
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}
Published to the official MCP Registry as `io.github.alikup-ai/otgate-opcua`, and to PyPI as `otgate`.
The registry name carries
opcuabecause its search matches on the server name only and does not index
descriptions, so a bare
otgateis 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):
| Variable | Default | Meaning |
|---|---|---|
OTGATE_BACKEND | fake | fake or asyncua |
OTGATE_POLICY | examples/reactor_policy.yaml | policy YAML path |
OTGATE_AUDIT | audit.jsonl | audit 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_PORT | 127.0.0.1 / 8770 / 8771 | HTTP bind host and ports |
Example MCP client config (FakeBackend):
{
"mcpServers": { "otgate": { "command": "otgate", "env": { "OTGATE_BACKEND": "fake" } } } }
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.
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.
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.
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