MCP server for industrial software that lets AI assistants connect machines, build screens and analyze production data
Standing AI teams that run whole business functions around the clock
Stage
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Founded
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Based in
TR
NZ
Pricing model
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Freemium
Pricing
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Free: 200 turns, 1 running team, up to 5 agents. Pay as you go: US$20 buys 2,000 turns. Starter: US$29/month with 2 running teams, up to 15 agents, 5,800 agent turns monthly. Business: US$99/month with 5 running teams, up to 50 agents, 19,800 agent turns monthly. Company: US$399/month with 20 runnin
Key features
Connect machines and create devices from plain language instructions
Build process screens and report dashboards that engineers review before deployment
Define production assets and calculate OEE for discrete, continuous or batch processes
Query alarm statistics and production data in natural language
Support MCP protocol over network HTTP or local stdio connections
Works with any MCP-compatible AI client including desktop and self-hosted models
Role-based access control matching viewer, operator and administrator permissions
Audit logging of every write operation with user identification
Acknowledge alarms and record batch results within user permissions
Generate Python code examples for REST API integration
Shadow mode for verification before live operation
Learns from documents, help centres and past tickets
Hard spending caps per team and job
Works with 102+ integrations
Kill switch to stop any team
Approval workflows for risky actions
Team memory and learning across jobs
MCP server and REST API for AI agents
Encrypted credential storage per connection
26+ ready-made teams for different functions
What makes it different
Built-in MCP server in every product, no separate AI add-on or cloud service needed
Production data remains on-premise; nothing sent to cloud unless user's chosen AI model requires it
Drafts protect production: AI-created screens and dashboards reviewed before going live
Same access controls for AI as for people: roles, rights and logging
Assists in user's own language and explains PLCGateway features through built-in help
Teams learn from your actual business documents and past work, not generic templates
Shadow mode proves capability before autonomous operation
You bring your own model key and pay providers directly, no markup
PLCGateway AI MCP
Jugg.ai