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Agentic interface for mainframes and COBOL

Hopper — AI Agents for Mainframe Operations - Hypercubic

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What is Agentic interface for mainframes and COBOL?

Hopper is an AI interface designed to connect artificial intelligence agents directly to mainframe systems running z/OS. It uses Anthropic's Model Context Protocol to allow teams to interact with mainframes through natural language instead of traditional command-line interfaces or COBOL code. This means developers and operators can describe what they want to accomplish in plain English, and the AI agents handle the underlying mainframe operations. The tool is particularly relevant for organisations with legacy mainframe infrastructure that want to modernise their workflows without replacing existing systems. It includes a development environment for building and customising agentic workflows tailored to your specific mainframe needs.

Key features

Natural language interface

Issue commands and queries to mainframes using everyday language rather than COBOL or JCL syntax

Model Context Protocol integration

Connects AI agents to z/OS systems for structured communication and task execution

Autonomous workflows

Create and deploy agents that can perform multi-step mainframe operations without manual intervention

Agentic development environment

Build custom agents and workflows specific to your organisation's mainframe requirements

Freemium model

Try the tool free with basic functionality before committing to paid tiers

Pros & cons

Advantages

  • Reduces technical barrier to mainframe operations by allowing natural language interaction instead of requiring COBOL expertise
  • Preserves existing mainframe investments whilst adding modern AI capabilities on top
  • Automates routine mainframe tasks through autonomous agents, reducing manual effort
  • Development environment lets teams build custom solutions tailored to their specific workflows

Limitations

  • Limited to z/OS systems; won't work with other mainframe platforms or legacy architectures
  • Requires careful security considerations when connecting AI agents to production mainframe systems
  • Learning curve for teams unfamiliar with agentic development patterns and Model Context Protocol concepts

Use cases

Automating routine batch job submissions and monitoring on mainframes

Querying mainframe databases and VSAM files through conversational AI instead of writing SQL or COBOL

Handling after-hours mainframe operations with autonomous agents that require minimal human oversight

Onboarding new team members by providing natural language access to complex mainframe systems

Building custom operational dashboards and alert systems that summarise mainframe status in plain language

Ready to try Agentic interface for mainframes and COBOL?

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Pricing

Free

Free

Basic access to Hopper interface and limited agentic operations per month

Pro

Contact for pricing

Higher operation limits, priority support, and access to advanced agentic development features

Enterprise

Contact for pricing

Unlimited operations, dedicated support, custom integrations, and on-premise deployment options

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