A powerful MCP server built with NitroStack
Add via Cursor Settings UI (Settings > Features > MCP > Add New MCP Server):
{
"mcpServers": {
// your other mcp servers
"forgeops-mcp": {
"url": "https://zenops-6a649dab-zen-net-amrita-university-coimbatore.app.nitrocloud.ai/mcp"
}
}
}
Connect remote tools directly via Claude's Web UI:
Configure custom tools directly via ChatGPT's Web UI:
Add the following configuration block under mcpServers in your Antigravity configuration file (~/.gemini/config/mcp_config.json):
{
"mcpServers": {
// your other mcp servers
"forgeops-mcp": {
"serverUrl": "https://zenops-6a649dab-zen-net-amrita-university-coimbatore.app.nitrocloud.ai/mcp"
}
}
}
Add the following configuration block to your Codex configuration file (~/.codex/config.toml):
[mcp_servers.forgeops-mcp] url = "https://zenops-6a649dab-zen-net-amrita-university-coimbatore.app.nitrocloud.ai/mcp"
Connect directly using the Server-Sent Events endpoint:
https://zenops-6a649dab-zen-net-amrita-university-coimbatore.app.nitrocloud.ai/mcp
Retrieve batch genealogy including route, timestamps, yield, material tracing, and production status from the Manufacturing Execution System.
Retrieve the stage-by-stage manufacturing path with cycle times, process parameters, and anomaly flags for a batch.
Retrieve queue delay events including wait times, expected wait, anomaly flags, and severity for a batch on a production line.
Retrieve machine alerts including vibration, temperature, and condition anomalies from the maintenance management system.
Retrieve current maintenance state, health score, service history, and open work orders for a machine.
Retrieve defect records with classes, severity, locations, measurements, and inspector notes from the quality management system.
Retrieve inspection results with quality scores, pass/fail criteria, and defect references.
Retrieve supplier and lot information including material specs, intake conditions, certifications, and storage requirements.
Retrieve material constraints: availability, lead times, supplier change freezes, alternative suppliers, and costs.
Run a counterfactual simulation scenario with modified parameters. Returns predicted yield, confidence, assumptions, and warnings if the scenario is outside the validated operating range.
Compare multiple simulation scenarios side-by-side with deltas against the baseline. Returns recommended scenario based on yield × confidence.
Get the full incident summary including affected batch, line, plant, severity, KPI change, causal chain, and current status.
Get the chronological event timeline across all data sources (MES, IoT, Maintenance, Quality) for the current incident.
Get the root cause analysis causal graph with nodes (factors), edges (causal relationships), influence scores, confidence levels, and evidence types.
Get ranked action recommendations with predicted yield, confidence, cost, risk, implementation difficulty, and evidence references.
Get the financial and operational impact analysis for the incident including current losses, recommended action savings, payback period.