MCP_IDMC — Informatica IDMC MCP Server

A FastMCP server that exposes Informatica Intelligent Data Management Cloud (IDMC) Data Integration APIs as MCP tools, allowing AI agents (Claude, etc.) to query, run, and monitor CDI mappings through natural language.

Tools

Data Integration (CDI)

Related MCP server: lol-mcp

Setup

1. Install dependencies

pip install -r requirements.txt

2. Configure credentials

cp .env.example .env

Edit .env:

IDMC_USER=your@email.com
IDMC_PASS=yourpassword

3. Run the server

python src/server.py

4. Register in Claude Code

Add to ~/.claude/mcp.json:

{
  "mcpServers": {
    "idmc": {
      "command": "python",
      "args": ["C:/path/to/MCP_IDMC/src/server.py"],
      "env": {
        "IDMC_USER": "your@email.com",
        "IDMC_PASS": "yourpassword"
      }
    }
  }
}

How it works

The server authenticates against the IDMC REST API (/ma/api/v2/user/login) and uses the returned serverUrl and icSessionId for all subsequent CDI calls. Sessions are valid for ~2 hours.

AI Agent (Claude)
     │
     │  MCP tool call
     ▼
FastMCP server (src/server.py)
     │
     │  IDMC REST API  /api/v2/mapping
     │                 /api/v2/job
     │                 /api/v2/activity/activityLog
     │                 /api/v2/activity/activityMonitor
     ▼
Informatica IDMC (CDI)

Project Structure

MCP_IDMC/
├── src/
│   └── server.py              # Main MCP server application
├── scripts/
│   └── generate_mapping_report.py  # Generate HTML reports from mapping exports
├── json/
│   └── mapping_sample.json    # Sample mapping metadata
├── output/
│   └── *.html                 # Generated HTML analysis reports
├── .env                       # Your IDMC credentials (not in git)
├── .env.example              # Template for credentials
├── requirements.txt          # Python dependencies
└── README.md                 # This file

Scripts

Mapping Report Generator

Generate a beautiful HTML analysis report from an exported IDMC mapping.

Usage:

1. Export your mapping from IDMC (Export > Mapping)

2. Extract the export package

3. Update paths in scripts/generate_mapping_report.py:

   • Path to the API mapping JSON (from get_mapping() or saved locally)

   • Path to the exported @3.bin file (usually in Explore/[Project]/[Folder]/[Mapping].DTEMPLATE.zip/bin/@3.bin)

4. Run the script:

   python scripts/generate_mapping_report.py

5. Find the generated HTML report in output/

The report includes:

• General mapping information (creator, timestamps, status)

• Transformation summary with counts by type

• Detailed transformation breakdown (Sources, Expressions, Aggregators, Targets)

• Visual data flow diagram

• Mapping purpose description

IDMC pod configuration

The server is pre-configured for the dm1-em pod:

To use a different pod, update LOGIN_URL and CAI_BASE_URL in src/server.py.

Requirements

• Python 3.10+

• fastmcp, mcp, requests

• An active Informatica IDMC account with CDI access