maximo-mcp-ai-integration

maximo-mcp-ai-integration

he Maximo MCP Server bridges AI agents (Claude, Cursor, Antigravity) with your IBM Maximo environment. It empowers your AI to autonomously discover Object Structures (APIs), inspect schemas, and query live data via OSLC. Instead of hallucinating field names, the AI validates queries instantly and ca

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README

<div align="center">

🏭 Maximo MCP Server

AI-Powered Development for IBM Maximo

Node.js MCP Maximo License Version

Transform your Maximo development workflow with AI-driven schema discovery, live data querying, and intelligent code generation.

Author: Markus van Kempen
Email: mvankempen@ca.ibm.com | markus.van.kempen@gmail.com
Date: 3 February 2026

Getting StartedDocumentationLive DemoUse Cases

</div>


🎯 What is This?

The Maximo MCP Server is a Model Context Protocol server that connects AI assistants (like Antigravity, Cursor, or VS Code Copilot) directly to your IBM Maximo environment. Instead of manually copying API documentation, the AI can:

Capability Description
🔍 Discover APIs Find available Object Structures (MXWO, MXASSET, etc.)
📋 Inspect Schemas Get exact field names, types, and descriptions
📊 Query Live Data Execute OSLC REST queries and see real results
🎨 Generate UI Create Carbon Design System tables and dashboards
Validate Instantly Test queries before generating final code

📚 Documentation

Core Guides

Document Description
📖 Maximo MCP Server Guide Complete setup, configuration, and tool reference
🔌 Maximo API Interaction Guide OSLC query syntax, code generation patterns, troubleshooting
🎬 Asset Manager Case Study Step-by-step walkthrough of building a complete app

French Translations

Document Description
📖 Guide du Serveur MCP Maximo Version française du guide complet
🔌 Guide d'Interaction API Maximo Version française du guide API

Word Documents

All guides are also available in .docx format in the docs/ folder for offline reading and sharing.


⚡ Quick Start

Prerequisites

  • Node.js v18 or higher
  • Maximo API Key with read access
  • AI IDE with MCP support (Antigravity, Cursor, VS Code + Continue)

Installation

Installation

Method 1: Run directly with npx (Recommended)

npx maximo-mcp-server

Method 2: Clone from Source

# Clone the repository
git clone https://github.com/markusvankempen/maximo-mcp-ai-integration-options.git
cd maximo-mcp-ai-integration-options

# Install dependencies
npm install

# Set up environment variables
cp .env.example .env
# Edit .env with your Maximo credentials

Environment Configuration

Edit the .env file with your Maximo credentials:

# .env (never commit this file!)
MAXIMO_URL=https://your-maximo-host.com/maximo/api
MAXIMO_HOST=https://your-maximo-host.com
MAXIMO_API_KEY=your-api-key-here
MAXIMO_OPENAPI_PATH=./maximo_openapi.json
PORT=3002

Download the OpenAPI Schema (Recommended)

The OpenAPI schema file enables offline schema lookups for faster AI responses:

# Download from your Maximo instance
curl -X GET "https://your-maximo-host.com/maximo/oslc/oas/api" \
     -H "apikey:your-api-key-here" \
     -o maximo_openapi.json

Alternatively, download via Swagger UI at: https://your-host/maximo/oslc/oas/api.html

Note: This file is ~12MB and contains all Object Structure definitions for your Maximo instance.

IDE Configuration

Copy and configure the MCP settings for your IDE:

For Cursor:

cp config/mcp_config.json.example ~/.cursor/mcp.json

For Antigravity:

mkdir -p .gemini && cp config/mcp_config.json.example .gemini/settings.json

Edit the config file and update the path to maximo-mcp-server.js:

{
  "mcpServers": {
    "maximo": {
      "command": "node",
      "args": ["/absolute/path/to/maximo-mcp-server.js"],
      "env": {
        "MAXIMO_URL": "https://your-maximo-host/maximo/api",
        "MAXIMO_API_KEY": "your-api-key-here"
      }
    }
  }
}

Verify Connection

In your AI IDE, ask:

"Is the Maximo MCP server connected?"

The AI will call get_instance_details and confirm connectivity.


🎬 Live Demo

Asset Manager Application

We built a complete Maximo Asset Manager web application using only natural language prompts and the MCP server.

<div align="center">

Asset Manager Dashboard

50 assets loaded with real-time filtering and search

</div>

Demo Features

Feature Screenshot
Full Dashboard 50 assets, 4 stat cards, 3 sites
Search Filter Pump Search
Site Filter LAREDO Filter

🎥 Screen Recording

A complete video demonstration is available: assets_demo_recording.webp

Try It Yourself

# Start the local proxy server
node server.js

# Open in browser
open http://localhost:3002/demos/assets.html

🛠 Available MCP Tools

The server exposes 6 tools to the AI:

MCP Tools UI

Tool Name Description
list_object_structures List available Maximo Object Structures (APIs)
get_schema_details Get field definitions for an Object Structure
query_maximo Execute OSLC REST queries
render_carbon_table Generate Carbon Design HTML tables
render_carbon_details Generate detail view for a record
get_instance_details Check server connectivity

💡 Use Cases

1. Generate API Calls

"Get me the last 10 approved work orders from BEDFORD site"

The AI calls get_schema_details(MXWO), understands the fields, and generates:

GET /maximo/api/os/mxwo
    ?oslc.where=status="APPR" and siteid="BEDFORD"
    &oslc.select=wonum,description,status,reportdate
    &oslc.orderBy=-reportdate
    &oslc.pageSize=10
    &lean=1

2. Generate Python Scripts

"Write a Python script to export all Priority 1 work orders to CSV"

import requests
import csv

response = requests.get(
    "https://your-host/maximo/api/os/mxwo",
    params={"oslc.where": "wopriority=1", "lean": 1},
    headers={"apikey": "YOUR_KEY"}
)

with open("priority1_workorders.csv", "w") as f:
    writer = csv.DictWriter(f, fieldnames=["wonum", "description"])
    writer.writeheader()
    writer.writerows(response.json()["member"])

3. Generate SQL Queries

"Write SQL to find overdue work orders"

SELECT wonum, description, status, targcompdate
FROM workorder
WHERE status NOT IN ('COMP', 'CLOSE', 'CAN')
  AND targcompdate < CURRENT_DATE;

4. Build Complete Applications

"Create an HTML dashboard to display assets"

Result: A complete web application with:

  • Dark theme with glassmorphism
  • Search and filter functionality
  • Interactive detail panels
  • Pre-loaded data from Maximo

See the Asset Manager Case Study for the full walkthrough.


📁 Project Structure

Maximo-MCP-EDF/
├── maximo-mcp-server.js       # 🔌 MCP Server implementation
├── server.js                  # 🌐 Local proxy server for CORS
├── package.json               # 📦 Dependencies
├── README.md                  # This file
├── .env.example               # Environment template
├── .gitignore                 # Git ignore rules
│
├── docs/                      # 📚 Documentation
│   ├── Maximo_MCP_Server_Guide.md         # Complete MCP guide
│   ├── Maximo_API_Interaction_Guide.md    # API interaction patterns
│   ├── Asset_Manager_App_Case_Study.md    # Build walkthrough
│   ├── Maximo_MCP_Server_Guide_FR.md      # French translation
│   └── Maximo_API_Interaction_Guide_FR.md # French translation
│
├── demos/                     # 🎨 Demo Applications
│   ├── assets.html                        # Asset Manager app
│   ├── carbon_workorders.html             # Carbon table demo
│   └── index.html                         # API visualization demo
│
├── images/                    # 📸 Screenshots & Recordings
│   ├── assets_demo_recording.webp         # Full demo recording
│   ├── assets_loaded.png                  # Dashboard screenshot
│   ├── pump_search_results.png            # Search demo
│   └── laredo_filtered.png                # Filter demo
│
└── config/                    # ⚙️ Configuration Templates
    └── mcp_config.json.example            # MCP config template

🔒 Security Best Practices

Practice Description
🔐 Local Execution MCP server runs on your machine; API keys never leave your environment
📖 Read-Only Keys Use limited-permission API keys for development
🔒 Environment Variables Never hardcode credentials in config files
🌐 HTTPS Only Always use encrypted connections to Maximo

🤝 Contributing

Contributions are welcome! Please read our contributing guidelines before submitting PRs.

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.


🙏 Acknowledgments

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