node-opcua-modeler-mcp-server
MCP serverAI & modelsThis addition gives your AI access to OPC UA reference data: type definitions from companion specifications, the namespaces those types depend on, and standard engineering units. Once added, your AI can look up these details whenever you ask about OPC UA types or units.
Use node-opcua-modeler-mcp-server in Claude, ChatGPT or Ahel Desktop
Free. Sign in, add node-opcua-modeler-mcp-server and connect your AI. About a minute.
Also: Claude Code · Cursor · Codex
Then ask your AI: use node-opcua-modeler-mcp-server to resolve dependencies
No key or account is asked for. Not verified by us yet: Ahel has not run a call through it.
Details
Available today. Use it from your connected AI after setup.
No key or account is asked for. Not verified by us yet: Ahel has not run a call through it.
Add it from the catalog, then ask your AI to look up OPC UA types, namespaces, or engineering units as you work.
What your AI can do with it
- Look up type definitions from OPC UA companion specifications
- Trace the namespace dependencies behind an OPC UA type
- Find the correct engineering unit for a measurement
Install node-opcua-modeler-mcp-server
The server’s own address, for the clients that take one directly. Or connect Ahel once and every client you use reads it from one address, with the account kept on Ahel rather than in each client’s config.
Claude Code
claude mcp add --transport http --scope user node-opcua-modeler-mcp-server 'https://api.opcua-modeler.sterfive.io/api/mcp'Run it once in your project, then open /mcp to approve any sign-in the server asks for.
Claude Desktop
https://api.opcua-modeler.sterfive.io/api/mcpAdd a custom connector in Settings, paste this address, and approve the sign-in.
Cursor
cursor://anysphere.cursor-deeplink/mcp/install?name=node-opcua-modeler-mcp-server&config=eyJ1cmwiOiJodHRwczovL2FwaS5vcGN1YS1tb2RlbGVyLnN0ZXJmaXZlLmlvL2FwaS9tY3AifQ==Open the link and Cursor adds the server at that address.
ChatGPT
https://api.opcua-modeler.sterfive.io/api/mcpIn Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.
Codex
codex mcp add node-opcua-modeler-mcp-server --url 'https://api.opcua-modeler.sterfive.io/api/mcp'Run it once, then sign in with codex mcp login node-opcua-modeler-mcp-server if the server asks for an account.
From the project's README
As published by node-opcua/node-opcua-modeler-mcp-server in README.md.
An MCP server that gives AI agents access to the OPC UA companion specification type system — 764 types across 30 industrial namespaces, plus 1,533 engineering units — and lets agents validate, generate, reverse-engineer, and create OPC UA information models.
Built on node-opcua, the most widely used OPC UA stack for Node.js.
Why?
When an AI agent needs to build an OPC UA information model, it must know:
- What companion spec types exist (DI, Machinery, Robotics, Machine Tools…)
- What components, properties, and methods each type has
- What namespace dependencies are required
- What engineering unit symbols are valid (UNECE Rec. 20)
This MCP server answers all of those questions — offline, for free, in milliseconds.
Quick Start
With Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"opcua-modeler": {
"command": "npx",
"args": ["-y", "node-opcua-modeler-mcp-server"],
"env": {
"OPCUA_MODELER_API_KEY": "stfv_your_api_key_here"
}
}
}
}
Note: The API key is optional for discovery tools (offline) and
opcua_model_validate(50 anonymous calls/day). It is required foropcua_model_generate,opcua_model_reverse, andopcua_model_create. Register at opcua-modeler.sterfive.io and create a key under Settings → API — the free tier gives 25 calls/day for 90 days; see pricing for paid plans.
With any MCP client
npx node-opcua-modeler-mcp-server
The server communicates over stdio using the Model Context Protocol.
Using a local backend instead of the hosted API
If you run the OPC UA Modeler CLI on the same machine, the model tools can be served from it instead of the hosted API — your YAML never leaves the host.
Start the server (requires a licence that includes the serve entitlement):
opcua-modeler serve
Then set one environment variable in your MCP client config:
{
"mcpServers": {
"opcua-modeler": {
"command": "npx",
"args": ["-y", "node-opcua-modeler-mcp-server"],
"env": {
"OPCUA_MODELER_BACKEND": "local"
}
}
}
}
No API key is needed in this mode — the client discovers the local endpoint and its credentials automatically.
| Variable | Values | Purpose |
|---|---|---|
OPCUA_MODELER_BACKEND | cloud (default), local | Which backend serves the model tools |
OPCUA_MODELER_API_KEY | stfv_… | API key, cloud backend only |
OPCUA_MODELER_API_URL | URL | Override the hosted API base URL |
Notes
- The two backends are never mixed, and there is no fallback between them. If
localis selected and no server is running, the call fails with instructions rather than silently sending your model to the hosted API. - The seven discovery tools are local to this package and work offline on either setting.
opcua_model_create(AI generation) is available on thecloudbackend only.
Tools
list_namespaces
List all 30 OPC UA companion spec namespaces with aliases, URIs, and dependencies.
→ list_namespaces()
← [
{ "alias": "di", "name": "OPC UA for Devices", "uri": "http://opcfoundation.org/UA/DI/", "dependencies": [] },
{ "alias": "robotics", "name": "OPC UA for Robotics", "uri": "http://opcfoundation.org/UA/Robotics/", "dependencies": ["di", "ia"] },
...
]
resolve_dependencies
Resolve the full dependency chain for companion spec aliases. Returns a topologically sorted list for the YAML namespaces: block.
→ resolve_dependencies({ aliases: ["machineTool"] })
← ["di", "ia", "machinery", "isa95JobControl", "machineryJobs", "machineTool"]
list_types
List all ObjectTypes and VariableTypes defined in a companion spec namespace.
→ list_types({ alias: "robotics" })
← [
{ "browseName": "MotionDeviceType", "kind": "ObjectType", "subtypeOf": "di:ComponentType", ... },
{ "browseName": "AxisType", "kind": "ObjectType", "subtypeOf": "di:ComponentType", ... },
...
] // 25 types
get_type_details
Get the full structure of a type — components, properties, methods, interfaces, including inherited members.
→ get_type_details({ alias: "robotics", browseName: "MotionDeviceType" })
← {
"browseName": "MotionDeviceType",
"kind": "ObjectType",
"subtypeOf": "di:ComponentType",
"interfaces": ["di:IVendorNameplateType", "di:ITagNameplateType"],
"components": [
{ "browseName": "robotics:Axes", "nodeClass": "Object", "typeDefinition": "FolderType", "modellingRule": "Mandatory" },
{ "browseName": "robotics:PowerTrains", "nodeClass": "Object", "typeDefinition": "FolderType", "modellingRule": "Mandatory" },
...
],
"properties": [
{ "browseName": "di:Manufacturer", "dataType": "LocalizedText", "modellingRule": "Mandatory" },
{ "browseName": "robotics:MotionDeviceCategory", "dataType": "MotionDeviceCategoryEnumeration", "modellingRule": "Mandatory" },
...
]
}
search_types
Search for types across all companion specs by keyword.
→ search_types({ query: "temperature" })
← [
{ "alias": "glass", "browseName": "MotorTemperatureTooHighEventType", ... },
{ "alias": "padim", "browseName": "TemperatureMeasurementVariableType", ... },
{ "alias": "amb", "browseName": "OverTemperatureConditionClassType", ... }
]
find_reusable_block
Find reusable Interfaces and AddIns by capability — pass a member name or keyword and get the standard blocks that already expose it. Prefer composing an existing block over redefining its members by hand.
→ find_reusable_block({ query: "SerialNumber" })
← [
{
"browseName": "di:IVendorNameplateType",
"alias": "di",
"kind": "interface",
"matchedMembers": ["di:SerialNumber"],
"members": ["di:Manufacturer", "di:Model", "di:SerialNumber", ...]
},
{
"browseName": "machinery:MachineIdentificationType",
"alias": "machinery",
"kind": "addin",
"matchedMembers": ["di:SerialNumber"],
"members": ["machinery:Location", "di:SerialNumber", ...]
}
]
kind tells you how to apply it: interface goes in interfaces:, addin in
addIns:.
find_engineering_unit
Find the official UNECE Rec. 20 engineering unit symbol. Supports fuzzy matching and natural language aliases.
→ find_engineering_unit({ query: "celsius" })
← { "symbol": "°C", "matchType": "alias", "confidence": 1 }
→ find_engineering_unit({ query: "revolutions per minute" })
← { "symbol": "r/min", "matchType": "alias", "confidence": 1 }
→ find_engineering_unit({ query: "bar" })
← { "symbol": "bar", "matchType": "exact", "confidence": 1 }
get_dsl_reference ☁️
Fetch the YAML DSL grammar reference — the file header, top-level sections, type and instance syntax, and a list of common mistakes. No API key required.
Served from the API rather than bundled into this package, so the reference an agent reads always matches the validator that will judge its output.
→ get_dsl_reference()
← { "version": "1", "reference": "# OPC UA Modeler YAML DSL ..." }
opcua_model_validate ☁️
Validate an OPC UA YAML model for correctness. Returns diagnostics with severity, codes, messages, and line numbers. Works without an API key (limited to 50 calls/day per IP).
→ opcua_model_validate({ yaml: "namespaces:\n di:\n..." })
← {
"valid": true,
"diagnostics": [
{ "severity": "warning", "code": "W001", "message": "...", "line": 42 }
]
}
opcua_model_generate ☁️
Generate OPC UA NodeSet2.xml and Symbols.CSV from a validated YAML model. Returns base64-encoded artifacts. Requires an API key.
→ opcua_model_generate({ yaml: "namespaces:\n di:\n...", include_docs: false })
← {
"valid": true,
"artifacts": {
"nodeset2_xml": "PD94bWwg...",
"symbols_csv": "bmFtZSxu..."
},
"diagnostics": []
}
opcua_model_reverse ☁️
Reverse-engineer a NodeSet2.xml file back into the YAML DSL format. Requires an API key.
→ opcua_model_reverse({ xml: "<?xml version=..." })
← {
"yaml": "namespaces:\n di:\n...",
"diagnostics": []
}
opcua_model_create ☁️
Generate an OPC UA YAML model from a natural language description using AI. The AI will auto-detect relevant companion specs, generate a validated model with documentation, and auto-correct validation errors. Requires an API key.
→ opcua_model_create({ prompt: "A robotic welding cell with two robot arms, each having 6 axes, temperature monitoring on each motor" })
← {
"success": true,
"yaml": "namespaces:\n di:\n robotics:\n...",
"attempts": 2,
"diagnostics": [],
"model": "gemini-2.5-pro",
"tokens": { "input": 4200, "output": 1800 }
}
→ opcua_model_create({ prompt: "A CNC lathe with spindle speed and temperature", forceSpecs: ["di", "cnc"] })
← {
"success": true,
"yaml": "namespaces:\n di:\n cnc:\n...",
"attempts": 1,
"diagnostics": [],
"model": "gemini-2.5-pro",
"tokens": { "input": 3500, "output": 1200 }
}
Coverage
Companion Specifications (30)
| Alias | Specification | Types |
|---|---|---|
padim | OPC UA for PA-DIM | 101 |
ijtBase | OPC UA for IJT Base | 65 |
machineTool | OPC UA for Machine Tools | 63 |
scales | OPC UA for Scales | 58 |
lads | OPC UA for Laboratory Devices | 53 |
di | OPC UA for Devices | 44 |
glass | OPC UA for Glass Manufacturing | 36 |
machineVision | OPC UA for Machine Vision | 36 |
adi | OPC UA for Analyzer Devices | 35 |
commercialKitchenEquipment | OPC UA for Commercial Kitchen Equipment | 35 |
i4aas | OPC UA for I4AAS | 32 |
robotics | OPC UA for Robotics | 25 |
ia | OPC UA for Industrial Automation | 20 |
amb | OPC UA for AMB | 18 |
autoId | OPC UA for AutoID | 18 |
iolink | OPC UA for IO-Link | 16 |
metalForming | OPC UA for Metal Forming | 16 |
| …and 12 more | ||
| Total | 29 namespaces with types | 764 types |
The registry holds 28 specs; irdi is a dictionary-entry namespace and
defines no ObjectTypes or VariableTypes. These figures come from
catalog/catalog.json and are asserted against it by
test/catalog-coverage.test.ts, so they cannot drift silently.
Engineering Units
1,533 official UNECE Rec. 20 symbols plus 136 natural language aliases (e.g., "celsius" → °C, "revolutions per minute" → r/min). Every alias resolves to a symbol the modeler engine accepts — the lookup never invents one.
How It Works
The server ships with a pre-generated catalog.json containing all type information extracted from OPC Foundation's official NodeSet2.xml files via node-opcua. All queries are answered from this static catalog — no network required, no API key needed.
┌──────────────────────────────────────────────────┐
│ node-opcua-modeler-mcp-server │
│ │
│ LOCAL TOOLS (offline, free) │
│ ┌────────────────────────────────────────┐ │
│ │ catalog.json (1.7 MB) │ │
│ │ • 30 companion spec registries │ │
│ │ • 764 type summaries + details │ │
│ │ • 1,533 engineering units │ │
│ └────────────────────────────────────────┘ │
│ 7 tools → query the catalog │
│ │
│ CLOUD TOOLS (via api.opcua-modeler.sterfive.io) │
│ 5 tools → reference / validate / generate / │
│ reverse / create │
│ │
│ stdio transport (JSON-RPC) │
└──────────────────────────────────────────────────┘
Use Cases
- AI-assisted OPC UA modeling — agents can discover types, resolve dependencies, and validate unit symbols before generating YAML/XML models
- Copilot integration — add OPC UA awareness to coding assistants
- Industrial digital twin design — explore companion spec type hierarchies interactively
- Learning OPC UA — ask an AI to explain types and their relationships
Requirements
- Node.js ≥ 18
Related
- OPC UA Modeler on GitHub — the open YAML DSL specification, the JSON Schema and example models; the place for questions and issues about the language
- OPC UA Modeler — web app — Create, validate, and generate OPC UA information models in the browser
- Product page — OPC UA Modeler overview, features, and licensing
- Documentation — Guides, YAML DSL reference, and how-tos
- Specification reference — Rendered OPC UA information-model specification
- node-opcua — Full OPC UA stack for Node.js
- Model Context Protocol — Open protocol for AI tool integration
Licensing
Three layers, stated once:
| What | Licence |
|---|---|
This package (node-opcua-modeler-mcp-server, the MCP client and its catalog) | Apache License 2.0 from version 1.5.0 — see NOTICE for trademark and third-party notices. Versions 1.0–1.4.x were published under MIT and remain so. |
The hosted OPC UA Modeler API (opcua-modeler.sterfive.io/api/v1) that the cloud backend calls | Sterfive API Terms of Use — anonymous discovery, free and paid plans. |
The OPC UA Modeler CLI and opcua-modeler serve (the local backend) | Sterfive commercial licence — see the product page. |
"OPC UA Modeler" and "Sterfive" are trademarks of Sterfive SAS; the Apache licence grants no rights to them. Contributions are accepted under the Developer Certificate of Origin.
Tools it offers (12)
What this server listed when Ahel dialed its public endpoint in Oct 2026, with no key and no account of yours. The names are the server’s own.
resolve_dependencieslist_namespaceslist_typesget_type_detailssearch_typesfind_reusable_blockfind_engineering_unitget_dsl_referenceopcua_model_validateopcua_model_generateopcua_model_reverseopcua_model_create
Signals
- GitHub stars
- 2
- Last commit
- Sep 2026
- Weekly downloads
- 63
- Weekly_downloads
- 94 weekly_downloads
Advanced
- Delivery
- node-opcua-modeler-mcp-server MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
- Item type
- mcp-server
- Key
io-github-node-opcua-node-opcua-modeler-mcp-server- Source
- github.com/node-opcua/node-opcua-modeler-mcp-server
- Hosted endpoint
https://api.opcua-modeler.sterfive.io/api/mcp
github.com/node-opcua/node-opcua-modeler-mcp-server
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