MCP_IDMC

MCP_IDMC

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

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README

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)

Tool Description
list_mappings Lists all Data Integration mappings in the org
get_mapping(mapping_id) Gets full metadata for a specific mapping
run_mapping_task(task_id) Triggers a mapping task by its task ID
get_job_status() Returns the status of all currently running jobs
get_activity_log(task_id, row_limit) Returns completed run history for a task

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:

Setting Value
Login URL https://dm1-em.informaticacloud.com/ma/api/v2/user/login
CDI API base <serverUrl>/api/v2/ (returned at login)
CAI base URL https://emc1-cai.dm1-em.informaticacloud.com/active-bpel/rt/

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

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