Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Gates an LLM agent's writes to an OPC UA server on ranges, rate of change and live interlocks.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
OTGATE_BACKEND, OTGATE_POLICY, OTGATE_AUDIT, OTGATE_SHADOW, OTGATE_RATE_HISTORY, OTGATE_OPCUA_ENDPOINT필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"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"
}
}
}
}터미널에서 이 명령어를 실행하세요
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 otgate실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"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"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"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"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
OTGATE_BACKEND envOTGATE_POLICY envOTGATE_AUDIT envOTGATE_SHADOW envOTGATE_RATE_HISTORY envOTGATE_OPCUA_ENDPOINT env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 8일 점검
레지스트리 이름이 GitHub 계정 alikup-ai 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.1.1)은 오늘 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요