135+ MCP Tools — Full Factory Access

Capacity utilization (CM01) for a machine by period (day/week).

Capacity overview of all machines. Identifies over-/under-utilized machines.

Compact capacity summary of all machines (current + next week).

Production orders per work center (CM21), filterable by machine.

Shift model for all departments: which shifts run when, net minutes, holidays.

Average capacity utilization in percent.

Lists all customer orders: customer, article, quantity, delivery dates, status.

Details of a customer order including production order and delivery status.

VA05 overview: total count, open, in production, shipped, overdue.

At-risk customer orders near delivery date or overdue.

Overall on-time delivery rate across all customers.

Detailed OTD statistics overall and per customer.

Monthly revenue from delivered customer orders.

All open fault and maintenance notifications.

Maintenance orders, optionally filtered by status.

Reliability metrics: MTBF, MTTR, availability.

PM overview: open notifications, orders, MTBF/MTTR.

Downtime analysis with reason codes and duration.

Requirements/stock list (MD04) for a part, similar to SAP MD04.

All current shortages (MD07) — parts with stock deficits.

Forecasts part availability at a specific date.

Shortages for assemblies (in-house production, not purchasable).

OEE of a machine: availability x performance x quality.

Latest OEE values for all machines.

Production history: good parts, scrap, rework per hour.

OEE summary per machine: avg, min, max, scrap rate over a period. Sorted worst first.

Scrap history grouped by machine.

Details of a work order including material and capacity status.

Machine queue: orders sorted by priority.

Check material availability for a work order.

Number of blocked orders (material/capacity).

All open purchase orders with expected delivery dates.

Supplier for a material with lead time and price.

Supplier evaluation: delivery reliability, quality, pricing.

Active SPC alarms with affected machines.

Measuring instruments with calibration due.

Open quality notifications (complaints, internal defects).

Process capability indices (Cpk) for all monitored characteristics.

Stock level of a material with reservations and availability.

Materials with low stock (below safety stock level).

Material coverage in days — which materials have the lowest reach based on stock vs. open demand.

Status of all tools: wear, location, availability.

All tools currently at a machine.

Tools with critical wear (>80%).

Replace a worn tool at a machine.

Available replacement tools for a tool type.

Tool list for an article — required tool types.

Checks if a machine has all required tools for an article.

Required tool changes for a changeover + additional setup time.

Recent tool usages and replacements.

Injection molding process data (~97 parameters): temperatures, pressures, speeds.

Trend of a process parameter over time — drift detection.

Cavity balance (pressure distribution) — detects uneven filling.

Trend of a cavity (hot runner temp, pressure) over time.

Hourly aggregates: averages, shot count, scrap rate.

Status of all assembly tools: wear, station, availability.

Assembly tools with critical wear (>80%).

All tools at an assembly station.

Replacement tools for an assembly tool type.

Replace a worn tool at an assembly station.

Recent tool usages at assembly stations.

Assembly line maintenance overview.

Open fault/maintenance notifications for assembly lines.

Open maintenance orders for assembly lines.

Reliability metrics: MTBF, MTTR, availability.

Due maintenance plans for assembly lines.

OEE of an assembly line (availability, performance, quality).

Process data of an assembly station (parameters, targets, tolerances).

Shop floor data: cycle times, good parts, NOK parts, fault reasons.

Energy consumption of all machines: current power draw, total kWh.

Energy consumption of a machine over time.

kWh per good part for a machine.

Energy costs in EUR.

Hourly power trend for a machine.

Base load vs. production load of all machines.

All subcontracting orders with status.

Capacity and utilization of subcontracting suppliers.

Orders ready for shipment to supplier.

Orders with expected goods receipt.

Delivery reliability of subcontracting suppliers.

Orders in queue by supplier.

Quality rating of subcontracting suppliers.

Status of pre-assembly cells VM-1, VM-2, VM-3.

OEE of pre-assembly cells.

Buffer fill levels between pre-assembly and assembly lines.

Maintenance status of pre-assembly stations.

Status of the test field (function test, leak test, burn-in).

Pass/fail rate of the test field.

Parts in the test field queue.

Defect analysis by defect type and product.

Time-series data for a machine variable over configurable hours.

Compare same variable between two machines.

Aggregated values (AVG/MIN/MAX) per granularity.

Find values deviating beyond N sigma from mean.

List all machines with historian data and data point counts.

List all recorded variables for a specific machine.

Trace downstream impact from a source node (up to 3 hops).

Find shortest path between two nodes.

Get all neighbor nodes within configurable depth.

Aggregate numeric property across a label.

Semantic search by natural language using vector embeddings.

Get complete KG schema — labels, relationships, properties.

Extract subgraph around a node within radius.

Filter nodes by label and property conditions.

Run a read-only Cypher query against the Knowledge Graph.

Quick summary: total nodes, edges, top labels, top relationship types.

Delivery feasibility snapshot — orders with materials, stock, machine capacity, OEE, customer info.

Generate a Chart.js visualization from a natural language question about the KG.

List all machines currently publishing UNS data via MQTT.

Get all current UNS values for a machine: BDE, ProcessData, OEE, Status.

Read a single UNS topic value by full topic path.

Get all values of a data category for a machine (BDE, ProcessData, QMS, WMS).

Search UNS topics by pattern with wildcards (* = single level, # = multi level).

Show all UNS values with non-good quality (faults, warnings, bad readings).

Get last N values of a UNS topic from ring buffer — shows trend.

Compare the same variable across multiple machines.

All machines auto-discovered from MQTT UNS.

All sensors on a discovered machine with last values.