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IBM i MCP Server

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MCP server for IBM i

Overview

The IBM i MCP Server enables AI agents to interact with IBM i systems through the Model Context Protocol (MCP). It provides secure, SQL-based access to Db2 for i databases, allowing AI applications like Claude, VSCode Copilot, Bob, and custom agents to query system information, monitor performance, and execute database operations.

MCP Architecture

How it works: AI clients connect via MCP β†’ Server executes YAML-defined SQL tools β†’ Results stream back to the AI agent through Mapepire.

TIP

πŸ“š

The Docs are continuously evolving. Please check back frequently for updates and new guides. If there's something missing, feel free to open an issue!

πŸ“ Repository Structure

Directory

Purpose

Documentation

server/

MCP server implementation (TypeScript)

Server README

tools/

YAML-based SQL tool configurations

Tools Guide

agents/

AI agent examples and integrations

Agents Guide

client/

Python client examples for testing

Client README

deployment/

Docker, Podman, OpenShift configs

Deployment Guide

πŸ“– Quick Navigation

πŸš€ MCP Server

The MCP Server enables AI agents to execute SQL queries on IBM i systems through YAML-defined SQL tools.

Quick Start

Prerequisites:

  • Mapepire running on IBM i (port 8076)

  • Node.js 18+ installed

Get Started:

  1. Clone the repository:

    git clone https://github.com/IBM/ibmi-mcp-server.git cd ibmi-mcp-server

  2. Configure your IBM i connection:

    cat > .env << 'EOF' DB2i_HOST=your-ibmi-host.com DB2i_USER=your-username DB2i_PASS=your-password DB2i_PORT=8076 DB2i_IGNORE_UNAUTHORIZED=true EOF

  3. Start the server:

    npx -y @ibm/ibmi-mcp-server@latest \ --transport http \ --tools ./tools/performance/performance.yaml

    The server will use our pre-configured tools for:

    • πŸ“Š Performance monitoring (system status, memory pools, active jobs)

    • See the Tools Guide for more toolsets.

  4. Verify it's running:

    # Check server health curl http://localhost:3010/healthz # List available tools curl -X POST http://localhost:3010/mcp \ -H "Content-Type: application/json" \ -H "Accept: application/json, text/event-stream" \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' | \ grep -o '"name":"[^"]*"' | sed 's/"name":"//g' | sed 's/"//g' | head -20
NOTE

πŸ“– Full Server Quickstart β†’

Next Steps:

Additional links:

🧩 SQL Tools

YAML-based SQL tool configurations that define what queries AI agents can execute on your IBM i system.

Quick Start

Create a custom tool file tools/my-tools.yaml:

sources: my-system: host: ${DB2i_HOST} user: ${DB2i_USER} password: ${DB2i_PASS} port: 8076 ignore-unauthorized: true tools: system_status: source: ibmi-system description: "Overall system performance statistics with CPU, memory, and I/O metrics" parameters: [] statement: | SELECT * FROM TABLE(QSYS2.SYSTEM_STATUS(RESET_STATISTICS=>'YES',DETAILED_INFO=>'ALL')) X toolsets: performance: tools: - system_status

Run the server with your tools:

npx -y @ibm/ibmi-mcp-server@latest --tools ./tools/my-tools.yaml --transport http

Available Tool Collections

The tools/ directory includes ready-to-use configurations:

  • Performance Monitoring - System status, active jobs, CPU/memory metrics

  • Security & Audit - User profiles, authorities, security events

  • Job Management - Active jobs, job queues, subsystems

  • Storage & IFS - Disk usage, IFS objects, save files

  • Database - Tables, indexes, constraints, statistics

NOTE

πŸ“– Full Documentation: Tools Guide β†’

Additional links:

πŸ€– AI Agents

Pre-built AI agent examples using popular frameworks to interact with IBM i systems through the MCP Server.

Available Agent Frameworks

Framework

Language

Use Case

Documentation

Agno

Python

Production-ready agents with built-in observability

Agno README

LangChain

Python

Complex workflows and tool chaining

LangChain README

Google ADK

Python

Google AI ecosystem integration

Google ADK README

What Agents Can Do

  • System Monitoring: Real-time performance analysis and health checks

  • Troubleshooting: Diagnose issues using natural language queries

  • Reporting: Generate system reports and insights

  • Automation: Execute administrative tasks through conversation

NOTE

πŸ“– Full Documentation: Agents Guide β†’

Additional links:

🐍 Python Clients

Simple Python client examples for testing and interacting with the MCP Server.

import asyncio from mcp import ClientSession from mcp.client.streamable_http import streamablehttp_client async def main(): # Connect to the IBM i MCP server with authentication async with streamablehttp_client("http://localhost:3010/mcp") as ( read_stream, write_stream, _, ): # Create a session using the authenticated streams async with ClientSession(read_stream, write_stream) as session: # Initialize the connection await session.initialize() # List available tools (now authenticated with your IBM i credentials) tools = await session.list_tools() for i, tool in enumerate(tools.tools, 1): print(f"{i:2d}. {tool.name}") print(f" └─ {tool.description}") # Execute a tool with authenticated IBM i access print("\n" + "=" * 80) print("SYSTEM ACTIVITY RESULT") print("=" * 80) result = await session.call_tool("system_activity", {}) print(result) if __name__ == "__main__": asyncio.run(main())
NOTE

πŸ“– Full Documentation: Client README β†’

Additional links:

πŸ“¦ Deployment

Production-ready deployment configurations for containerized environments.

Deployment Options

  • Docker & Podman - Complete stack with MCP Context Forge Gateway

  • OpenShift - Kubernetes deployment with S2I builds

  • Production Features - HTTPS, authentication, monitoring, caching

NOTE

πŸ“– Full Documentation: Deployment Guide β†’

πŸ“‘ Setup Mapepire

Before you can use the ibmi-mcp-server, you must install and configure Mapepire on your IBM i system.

What is Mapepire?

Mapepire is a modern, high-performance database server for IBM i that provides SQL query execution capabilities over WebSocket connections. It acts as a gateway between modern application architectures (like MCP servers, AI agents, and REST APIs) and IBM i's Db2 for i database.

Why Mapepire Enables AI and MCP Workloads

Traditional IBM i database access methods (ODBC, JDBC) don't align well with modern AI and MCP architectures that require:

  • Fast, lightweight connections: AI agents make frequent, short-lived database queries

  • WebSocket support: Enables real-time, bidirectional communication for streaming results

  • Modern JSON-based protocols: Simplifies integration with TypeScript/JavaScript ecosystems

  • Low-latency responses: Essential for interactive AI conversations and tool executions

Mapepire bridges this gap by providing a modern, WebSocket-based SQL query interface that's optimized for the request/response patterns of AI agents and MCP tools.

Installation

Quick Install (IBM i SSH Session):

# 1. Install Mapepire using yum yum install mapepire-server # 2. Install Service Commander (if not already installed) yum install service-commander # 3. Start Mapepire service sc start mapepire
NOTE

πŸ“š Full Documentation: Mapepire System Administrator Guide β†’

IMPORTANT

Important Notes:

  • By default, Mapepire runs on port 8076. You'll need this port number when configuring the DB2i_PORT variable in your .env file.

  • Ensure your IBM i firewall allows inbound connections on port 8076

  • For production deployments, configure SSL/TLS certificates (see official guide)

πŸ“œ License

This project is licensed under the Apache License 2.0. See the LICENSE file for details.

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