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IBM i MCP Agents

AI agents for IBM i system administration and monitoring using Model Context Protocol (MCP) tools. This directory contains multiple agent framework implementations, deployment infrastructure, and web interfaces for interacting with intelligent IBM i system agents.

Agent Capabilities

All agent frameworks connect to the IBM i MCP server and can perform tasks such as:

  • System Performance Monitoring

    • CPU and memory utilization analysis
    • Job queue monitoring
    • Resource bottleneck identification

  • System Administration

    • Active job management
    • System configuration queries
    • Service status checks

  • Database Operations

    • Table and schema exploration
    • Data retrieval and analysis

Getting Started

Prerequisites

  • Python 3.12+ (for agent frameworks)
  • uv (Python package manager)
  • Node.js 20+ (for Agent UI)
  • MCP Server running in HTTP mode

Available Agent SDKs

The frameworks/ directory provides different agent SDK implementations, allowing you to choose the best solution for your use case.

SDK Language Status Documentation
Agno Python ✅ Active frameworks/agno/README.md
LangChain Python ✅ Active frameworks/langchain/README.md
Google ADK Python ✅ Active frameworks/google_adk/README.md

Deployment Infrastructure

Deploy IBM i agents using Agno AgentOS stack with Docker.

Documentation: See docker/ibmi-agent-infra/README.md

What's Included:

  • AgentOS API: RESTful API for agent interactions
  • IBM i MCP Server: Automatically configured and running
  • PostgreSQL Database: Session and memory persistence
  • Agent UI: Optional web interface
  • Multi-provider LLM Support: watsonx, OpenAI, Anthropic

Resources

For general IBM i MCP server issues, see the main project documentation.