Context7
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Description from the maker (original English)
Gates an LLM agent's writes to an OPC UA server on ranges, rate of change and live interlocks.
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Pick the AI app you use, then copy the settings.
OTGATE_BACKEND, OTGATE_POLICY, OTGATE_AUDIT, OTGATE_SHADOW, OTGATE_RATE_HISTORY, OTGATE_OPCUA_ENDPOINTYou need
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Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into 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"
}
}
}
}Run this in your terminal
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 otgateFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.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"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"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"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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OTGATE_BACKEND envOTGATE_POLICY envOTGATE_AUDIT envOTGATE_SHADOW envOTGATE_RATE_HISTORY envOTGATE_OPCUA_ENDPOINT envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026
The registry name was verified with the GitHub account alikup-ai, which owns the repo
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Runs on your computer and uses local settings instead
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The GitHub repo last changed –, and the latest version (0.1.1) reached the registry today.
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In the same category: Context7, Codebase Memory, Exa
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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
Only the beginning is shown; read the rest in the repo