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systemlink-mcp

systemlink-mcp

systemlink-mcp

An MCP server that exposes NI SystemLink to AI clients with test-and-measurement-native tools: yield by product revision, failing DUT steps versus spec limits, measurement-trace summaries, and calibration-due assets.

This is the fleet/data-layer companion to daq-mcp. daq-mcp talks to a single DAQ device. systemlink-mcp queries and correlates results, assets, and systems across a lab.

This is a personal project with one maintainer. It is not an NI product and is not affiliated with, endorsed by, or supported by NI / Emerson.

Why test-domain tools instead of a generic wrapper

A commercial middleware catalog can list SystemLink among thousands of industrial systems and then expose a CMMS/ERP-shaped surface: work orders, sites, spaces, sales orders. That abstraction cannot answer what a test engineer actually asks:

  • pass/fail rates for product revision B this quarter

  • which measurement on a failing DUT exceeded its limit

  • which PXI module is past its calibration due date

Every tool here is shaped around those questions. Responses are summaries plus a bounded preview, not raw Test Monitor or DataFrame payloads. Dumping thousands of result rows or a 2000-point waveform into a model context makes the server unusable even if the API calls are correct.

Related MCP server: Auto-Manager MCP

Read-only by default

Mutating tools (update_result_properties, execute_notebook) refuse unless SYSTEMLINK_MCP_ALLOW_WRITE=1. Read tools work with no extra flags.

The current nisystemlink-clients AssetManagementClient has create, query, delete, file-link, and utilization methods, but no asset update method. The gated write surface therefore updates Test Monitor result metadata and queues notebook executions, not asset records.

Stack

Python 3.11+, uv, FastMCP (stdio or Streamable HTTP), Pydantic v2, and the official nisystemlink-clients package. Tools never import the SDK; they call a SystemLinkBackend. Set SYSTEMLINK_MCP_SIMULATE=1 for a pure-Python fake that needs no SystemLink server.

uv sync
SYSTEMLINK_MCP_SIMULATE=1 uv run server.py

PowerShell:

$env:SYSTEMLINK_MCP_SIMULATE="1"; uv run server.py

The simulated backend is only used when SYSTEMLINK_MCP_SIMULATE=1, or when a live connect fails and SYSTEMLINK_MCP_REQUIRE_REAL is unset. A live response has "backend": "systemlink" and "simulated": false.

  1. Create an API key in SystemLink (Enterprise: a policy, then an API key; the HTTP header the SDK sends is x-ni-api-key). SLE does not accept username and password for programmatic access.

  2. Copy .env.example to .env (gitignored) and set:

SYSTEMLINK_SERVER_URI=https://your-systemlink-host
SYSTEMLINK_API_KEY=...
SYSTEMLINK_MCP_REQUIRE_REAL=1

Leave SYSTEMLINK_MCP_SIMULATE unset. On-prem SystemLink Server that still allows basic auth can use SYSTEMLINK_USERNAME / SYSTEMLINK_PASSWORD instead of a key. SystemLink Cloud can use the API key alone (no URI); the backend then constructs CloudHttpConfiguration.

  1. Probe before MCP so a failed login cannot silently become the fake fleet:

uv run server.py --probe

You should see "simulated": false and a short query_systems preview from your server. Then launch MCP without the simulate flag, or point Cursor at .cursor/mcp.json.live.example.

If --probe fails, the JSON error is from the SDK (ApiException / connect), not from dummy data.

Tools

Tool

Access

What it answers

summarize_yield

read

Pass/fail yield, optionally grouped by part, program, or serial

query_results

read

Filtered result counts plus a bounded recent preview

get_failing_steps

read

Failing steps for one result, with measurement vs limits

summarize_measurement

read

Table stats plus a downsampled trace (decimated on the live API)

list_calibration_due

read

Assets past or approaching calibration due

query_assets

read

Inventory with presence and calibration status

query_systems

read

Registered systems and connection health

query_products

read

Products / part numbers / families

query_specs

read

Spec limits for a product

list_files

read

File metadata for a result or asset (no contents)

update_result_properties

gated write

Keywords/properties on a test result

execute_notebook

gated write

Queue a Jupyter notebook execution

MCP Inspector

From the repo root, with simulation forced:

SYSTEMLINK_MCP_SIMULATE=1 npx -y @modelcontextprotocol/inspector uv run server.py

PowerShell:

$env:SYSTEMLINK_MCP_SIMULATE="1"
npx -y @modelcontextprotocol/inspector uv run server.py

Open the printed URL (typically http://127.0.0.1:6274). Confirm the twelve tools appear, then call summarize_yield with group_by=part_number.

Streamable HTTP instead of stdio:

SYSTEMLINK_MCP_SIMULATE=1 uv run server.py --http

The MCP endpoint is http://127.0.0.1:8000/mcp. Do not use transport="sse"; that transport is deprecated.

Cursor

Use .cursor/mcp.json.example (simulator) or .cursor/mcp.json.live.example (real server). Machine-local .cursor/mcp.json is gitignored.

{
  "mcpServers": {
    "systemlink-mcp": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "C:/Users/folayaod/personal/systemlink-mcp",
        "server.py"
      ],
      "env": {
        "SYSTEMLINK_MCP_SIMULATE": "1"
      }
    }
  }
}

Claude Desktop

Same JSON block, in claude_desktop_config.json:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Restart Claude Desktop after saving.

Prompts that exercise the simulated fleet

  1. "What is the pass/fail yield for part number PN-5164-B, grouped against the other revisions?"

  2. "DUT-1001 failed BoardFunctional.seq. Which step failed, and how did Gain compare to its limits? Summarize the attached measurement trace."

  3. "Which PXI assets are overdue or approaching calibration, and is PXI Rack 1 connected?"

Tests

SYSTEMLINK_MCP_SIMULATE=1 uv run pytest

Tests hit the simulated backend only. They do not open a network connection to SystemLink.

Status

Personal project, one maintainer. The simulated backend is the supported day-to-day path. The real backend is written against nisystemlink-clients 2.32.x APIs documented at python-docs.systemlink.io and the ni/nisystemlink-clients-python source. It has not been run against a live SystemLink Enterprise instance in this repository's CI. Asset Dynamic LINQ property names for calibration status follow the PascalCase style of the official AssetIdentifier example; if a live server rejects that filter, that is a known integration risk documented in DEVLOG.md.

Available Tools

12 tools
execute_notebookA

Start a SystemLink Jupyter notebook execution. Requires SYSTEMLINK_MCP_ALLOW_WRITE=1.

Uses NotebookClient.create_executions. This queues work on the server; it does not wait for completion or return notebook output.

notebook_id: Notebook id to run. workspace_id: Workspace the execution belongs to. parameters: Optional notebook parameters (values are stringified for the SDK).

Inputs: notebook_id (required), workspace_id (required), parameters. Returns: object

get_failing_stepsA

Return failing steps for one test result, with measurements versus limits.

This is the DUT-debug view: which step failed and how the measurement compared to the spec window. Step payloads are summarized; only failing steps are previewed.

result_id: Test Monitor result id. preview_limit: Max failing steps to include (capped at 50).

Inputs: result_id (required), preview_limit. Returns: object

list_calibration_dueA

List instruments whose calibration is overdue or approaching due.

This is the PXI-fleet question a generic CMMS wrapper cannot ask: which chassis or module needs cal, and when. Default statuses are PAST_RECOMMENDED_DUE_DATE and APPROACHING_RECOMMENDED_DUE_DATE.

include_out_for_calibration: Also include OUT_FOR_CALIBRATION assets. preview_limit: Max assets to include (capped at 50).

Inputs: preview_limit, include_out_for_calibration. Returns: object

list_filesA

List file metadata attached to a result or asset. Does not download contents.

file_ids: Explicit file ids. result_id: Test result whose file_ids should be listed. asset_id: Asset whose linked files should be listed. preview_limit: Max files to include (capped at 50).

Inputs: asset_id, file_ids, result_id, preview_limit. Returns: object

query_assetsA

Query the asset inventory: model, serial, presence, and calibration state.

name: Substring match on asset name. serial_number: Exact serial. model_name: Substring match on model, e.g. PXIe-6368. calibration_status: OK, APPROACHING_RECOMMENDED_DUE_DATE, PAST_RECOMMENDED_DUE_DATE, or OUT_FOR_CALIBRATION. preview_limit: Max assets to include (capped at 50).

Inputs: name, model_name, preview_limit, serial_number, +1 more. Returns: object

query_productsB

Query products and part numbers used to correlate test results by revision.

family: Product family, e.g. Oscilloscopes. part_number: Exact part number / revision. name: Exact product name. preview_limit: Max products to include (capped at 50).

Inputs: name, family, part_number, preview_limit. Returns: object

query_resultsA

Query test results and return counts plus a bounded recent preview.

Does not dump the full result set. Counts use Test Monitor return_count; the preview is the newest matching results only.

part_number: Product revision / part number. program_name: Test program or sequence name. serial_number: DUT serial. status: Optional status.statusType filter (PASSED, FAILED, ERRORED, ...). started_after: Inclusive ISO-8601 UTC start. started_before: Inclusive ISO-8601 UTC end. preview_limit: Max result rows to include (capped at 50).

Inputs: status, part_number, program_name, preview_limit, +3 more. Returns: object

query_specsA

Query specification limits for a product (min / typical / max, unit).

product_id: Product id or, in simulation, the part number used as product_id. preview_limit: Max specs to include (capped at 50).

Inputs: product_id (required), preview_limit. Returns: object

query_systemsA

Query registered test systems and their connection health.

alias: System alias or id substring. connected: If set, filter on status.data.http_connected. preview_limit: Max systems to include (capped at 50).

Inputs: alias, connected, preview_limit. Returns: object

summarize_measurementB

Summarize a measurement table: stats plus a downsampled trace preview.

On a live server this uses DataFrameClient.query_decimated_data rather than downloading every row. Pass table_id directly, or result_id to use the first attached data table.

table_id: DataFrame table id. result_id: Test result whose data_table_ids should be used if table_id is omitted. preview_limit: Max preview points (capped at 100).

Inputs: table_id, result_id, preview_limit. Returns: object

summarize_yieldA

Summarize pass/fail yield for test results.

Uses Test Monitor result-level status, not CMMS work-order counts. Filters are pushed to the server as Dynamic LINQ (partNumber, programName, serialNumber, status.statusType, startedAt). Yield is passed / (passed + failed).

part_number: Product revision / part number, e.g. PN-5164-B. program_name: Test program or sequence name, e.g. BoardFunctional.seq. serial_number: DUT serial. status: Optional status.statusType filter (PASSED, FAILED, ERRORED, ...). started_after: Inclusive ISO-8601 UTC start, e.g. 2026-01-01T00:00:00Z. started_before: Inclusive ISO-8601 UTC end. group_by: Break yield down by part_number, program_name, serial_number, or none.

Inputs: status, group_by, part_number, program_name, +3 more. Returns: object

update_result_propertiesA

Update keywords or properties on a test result. Requires SYSTEMLINK_MCP_ALLOW_WRITE=1.

Uses TestMonitorClient.update_result. Asset metadata cannot be patched through the current AssetManagementClient, which has no update method.

result_id: Test Monitor result id. keywords: Replacement keyword list if provided. properties: Properties to merge onto the result.

Inputs: result_id (required), keywords, properties. Returns: object

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4.1/5.0

    Scored across 12 tools

    Disambiguation5/5

    Each tool targets a distinct resource and action: yield aggregation, result queries, step-level failure analysis, measurement statistics, calibration status, asset/system/product/spec queries, file listing, result property updates, and notebook execution. There is no overlap; even query_results and summarize_yield differ clearly (raw counts vs pass/fail ratio). Descriptions explicitly disambiguate boundaries.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case: summarize_yield, query_results, get_failing_steps, list_calibration_due, execute_notebook, etc. Retrieval verbs vary (query vs list vs get) but are semantically appropriate and predictable, with no mixing of conventions.

    Tool Count5/5

    Twelve tools is well within the ideal 3–15 range and appropriately scoped for a SystemLink MCP server covering test data, asset management, and notebook execution. Each tool adds distinct value; none feel redundant or superfluous.

    Completeness4/5

    The surface covers the core read workflows (yield, results, failing steps, measurements, assets, systems, products, specs, files) plus limited write actions (update_result_properties, execute_notebook). Notable gaps include lack of update/delete for assets (acknowledged as unsupported by the underlying client), no single-result full detail view beyond failing steps, and no creation of test results. However, these are minor for the apparent purpose of monitoring and analysis.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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