bridge-mcp-server

Cross-platform intelligence bridge — correlate Ignition SCADA tags with Studio 5000 PLC logic end-to-end.

What This Does

bridge-mcp-server connects ignition-mcp-server and studio5000-mcp-server to answer questions like:

"This Ignition alarm fires when tag X goes true — here's the PLC logic that drives X"
"Which PLC tags are mapped to Ignition but have no OPC reference?"
"Trace this SCADA tag all the way down to the ladder rung that controls it"

It maps Ignition OPC tag paths to L5X tag names using convention-based normalization (with optional explicit mapping file override), then leverages the Studio 5000 cross-reference engine to find every line of PLC logic that references the matched tag.

Part of Project Automate by Nodeblue.

Installation

pip install bridge-mcp-server

This automatically installs both ignition-mcp-server and studio5000-mcp-server as dependencies.

Quick Start

stdio (local)

bridge-mcp-server

SSE (remote)

bridge-mcp-server --transport sse --port 8082

Configuration

kiro-cli

{
  "mcpServers": {
    "bridge": {
      "command": "bridge-mcp-server",
      "args": []
    }
  }
}

Available Tools

`ping`

Health check. Returns "pong".

`correlate_projects(ignition_path, l5x_path, mapping_file?)`

Build a full correlation map between an Ignition project and an L5X PLC project.

correlate_projects("/path/to/ignition-project", "/path/to/plc.l5x")

Returns:

{
  "matched": [
    {
      "ignitionPath": "Conveyors/Line1/Running",
      "opcItemPath": "ns=1;s=[PLC]Motor_1.Running",
      "l5xTag": "Motor_1",
      "l5xMember": "Motor_1.Running",
      "l5xDataType": "Motor_UDT",
      "l5xScope": "controller"
    }
  ],
  "ignitionOnly": [],
  "l5xOnly": [
    {"name": "EmergencyStop", "dataType": "BOOL", "scope": "controller"}
  ],
  "stats": {"matched": 3, "ignitionOnly": 0, "l5xOnly": 5}
}

`trace_tag(ignition_path, l5x_path, tag_name, mapping_file?)`

Deep end-to-end trace of a single tag from SCADA to PLC logic.

trace_tag("/path/to/ignition-project", "/path/to/plc.l5x", "Running")

Returns the complete signal chain: Ignition tag config → OPC item path → L5X tag details → every rung/line of PLC logic that references it.

`find_unmapped_tags(ignition_path, l5x_path, mapping_file?)`

Identify commissioning gaps — tags that exist on one side but not the other.

find_unmapped_tags("/path/to/ignition-project", "/path/to/plc.l5x")

OPC Path Mapping

The bridge uses convention-based mapping by default:

| Ignition OPC Item Path | L5X Tag Name | |---|---| | ns=1;s=[PLC]Motor_1.Running | Motor_1.Running | | [PLC]Motor_1.Running | Motor_1.Running | | [PLC]Program:MainProgram.StartPB | Program:MainProgram.StartPB | | Motor_1.Running | Motor_1.Running (passthrough) |

For complex setups (aliased tags, scaled values), provide a JSON mapping file:

{
  "ns=1;s=[PLC]Custom_Alias": "Motor_1.Running",
  "ns=1;s=[PLC]Scaled_Speed": "LineSpeed"
}

Pass it via mapping_file parameter on any tool.

Example Conversation

You: What PLC logic drives the Conveyors/Line1/Running tag in Ignition?

Agent calls: trace_tag("/projects/MyPlant", "/plc/MainPLC.l5x", "Running")

Agent: The Ignition tag Conveyors/Line1/Running maps to PLC tag Motor_1.Running
via OPC path ns=1;s=[SampleController]Motor_1.Running.

Motor_1 is a Motor_UDT instance. Motor_1.Running is referenced in:
- MainProgram/MainRoutine rung 1: Motor_Control AOI call
- MainProgram/MainRoutine rung 2: Fault detection branch
- MainProgram/FaultHandler line 1: IF Motor_1.Faulted THEN...

The Motor_Control AOI sets Running from MotorFeedback (rung 4).

Project Structure

src/bridge_mcp_server/
├── __init__.py       # v0.4.0
├── __main__.py       # CLI entry point (stdio/SSE)
├── server.py         # FastMCP with 4 tools (ping + 3 correlation tools)
└── correlator.py     # OPC path normalizer + correlation engine

tests/
└── test_correlator.py

Development

git clone https://github.com/nodeblue-ai/bridge-mcp-server.git
cd bridge-mcp-server
pip install -e .
pip install pytest
pytest tests/ -v

License

MIT

Built by Nodeblue — Engineering-driven technology across software, industrial automation, and applied research.

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