Delphix DCT API MCP Server

The Delphix DCT API MCP Server provides a robust Model Context Protocol (MCP) interface for interacting with the Delphix Data Control Tower (DCT) API. This service enables AI assistants and client applications to securely access test data management capabilities through a structured toolset.

Features

Comprehensive DCT integration: Access datasets, environments, engines, compliance, jobs, and reporting through specialized tools.
Security and reliability: API client includes retry logic, exponential backoff, and SSL configuration.
Flexible configuration: Environment-based setup with validation.
Cross-platform support: Startup scripts for Windows, macOS, and Linux.
Structured logging: Application and session logging with telemetry tracking.
Telemetry (Optional): Usage analytics are disabled by default and require user consent.

Quick Start

Configure the MCP server within your AI client application (such as Claude Desktop, Cursor, or VS Code). This is the recommended method and does not require separate installation.

What you need:

Delphix DCT Instance: Running Delphix Data Control Tower instance
API Key: Valid DCT API key with the following READ permissions:
- VDBs
- VDB Groups
- dSources
- Environments
- Bookmarks
- Snapshots
- Data Connections
- Engines
- Virtualization and Compliance Job Executions
- All Virtualization Storage Insights
uv (recommended): Install using uv. This method provides access to the uvx command.
OR Python 3.11+: If not using uv/uvx

Next step: Proceed to MCP Client Configuration to complete setup.

Alternative: To run the server as a standalone command-line tool or contribute to development, see Advanced Installation.

Videos

Watch these videos to see the MCP Server in action:

Environment Variables

All configuration methods use these environment variables:

DCT_API_KEY - Your Delphix DCT API key (required).

Do not prefix with apk. Use the key exactly as provided by DCT. Example: 2.123abc...
DCT_BASE_URL - Your DCT instance URL (required).

Do not append with /dct. Example: https://dct-hostname.com
DCT_VERIFY_SSL - Enable SSL verification (true/false, default: false)
DCT_LOG_LEVEL - Logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)
DCT_TIMEOUT - Request timeout in seconds (default: 30)
DCT_MAX_RETRIES - Maximum retry attempts (default: 3)
IS_LOCAL_TELEMETRY_ENABLED - Enable telemetry (true/false, default: false)

MCP Client Configuration

Note: Use absolute paths for the command field in all configurations. Ensure environment variables are set for each client application.

Configuration examples for popular MCP clients are provided below. The structure may vary (some use mcpServers, others use servers).

Configuration Methods

All clients support three installation methods:

Using uvx (Recommended):

Requires uv. Handles dependencies automatically.
Using Python directly:

Point to the main.py file in your local repository clone.
Using shell/batch scripts

Use provided startup scripts (_python.sh for Linux/macOS, _python.bat for Windows). The _uv.sh and _uv.bat scripts require uv.

See below for the full JSON configuration examples for each client.

Claude Desktop

Option 1: Using uvx (Recommended)

{
  "mcpServers": {
    "delphix-dct": {
      "command": "uvx",
      "args": ["--from", "git+https://github.com/delphix/dxi-mcp-server.git", "dct-mcp-server"],
      "env": {
        "DCT_API_KEY": "your-api-key-here",
        "DCT_BASE_URL": "https://your-dct-host.company.com",
        "DCT_VERIFY_SSL": "true",
        "DCT_LOG_LEVEL": "INFO"
      }
    }
  }
}

Option 2: Using Python directly

{
  "mcpServers": {
    "delphix-dct": {
      "command": "python",
      "args": ["/absolute/path/to/dxi-mcp-server/src/dct_mcp_server/main.py"],
      "env": {
        "DCT_API_KEY": "your-api-key-here",
        "DCT_BASE_URL": "https://your-dct-host.company.com",
        "DCT_VERIFY_SSL": "true"
      }
    }
  }
}

Option 3: Using shell/batch scripts

{
  "mcpServers": {
    "delphix-dct": {
      "command": "/absolute/path/to/dxi-mcp-server/start_mcp_server_uv.sh",
      "env": {
        "DCT_API_KEY": "your-api-key-here",
        "DCT_BASE_URL": "https://your-dct-host.company.com",
        "DCT_VERIFY_SSL": "true"
      }
    }
  }
}

Cursor IDE & Windsurf

Option 1: Using uvx (Recommended)

{
  "mcpServers": [
    {
      "name": "delphix-dct", 
      "command": "uvx",
      "args": ["--from", "git+https://github.com/delphix/dxi-mcp-server.git", "dct-mcp-server"],
      "env": {
        "DCT_API_KEY": "your-api-key-here",
        "DCT_BASE_URL": "https://your-dct-host.company.com",
        "DCT_VERIFY_SSL": "true",
        "DCT_LOG_LEVEL": "INFO"
      }
    }
  ]
}

Option 2: Using Python directly

{
  "mcpServers": [
    {
      "name": "delphix-dct",
      "command": "python",
      "args": ["/absolute/path/to/dxi-mcp-server/src/dct_mcp_server/main.py"],
      "env": {
        "DCT_API_KEY": "your-api-key-here",
        "DCT_BASE_URL": "https://your-dct-host.company.com",
        "DCT_VERIFY_SSL": "true"
      }
    }
  ]
}

Option 3: Using shell scripts

{
  "mcpServers": [
    {
      "name": "delphix-dct",
      "command": "/absolute/path/to/dxi-mcp-server/start_mcp_server_uv.sh",
      "env": {
        "DCT_API_KEY": "your-api-key-here",
        "DCT_BASE_URL": "https://your-dct-host.company.com",
        "DCT_VERIFY_SSL": "true"
      }
    }
  ]
}

Note: Windsurf uses the same configuration format as Cursor (mcpServers object).

VS Code, Eclipse, & IntelliJ IDEA

Option 1: Using uvx (Recommended)

{
  "servers": {
    "delphix-dct": {
      "command": "uvx",
      "args": ["--from", "git+https://github.com/delphix/dxi-mcp-server.git", "dct-mcp-server"],
      "env": {
        "DCT_API_KEY": "your-api-key-here",
        "DCT_BASE_URL": "https://your-dct-host.company.com",
        "DCT_VERIFY_SSL": "true",
        "DCT_LOG_LEVEL": "INFO"
      }
    }
  }
}

Option 2: Using Python directly

{
  "servers": {
    "delphix-dct": {
      "command": "python",
      "args": ["/absolute/path/to/dxi-mcp-server/src/dct_mcp_server/main.py"],
      "env": {
        "DCT_API_KEY": "your-api-key-here",
        "DCT_BASE_URL": "https://your-dct-host.company.com",
        "DCT_VERIFY_SSL": "true"
      }
    }
  }
}

Option 3: Using shell scripts

{
  "servers": {
    "delphix-dct": {
      "command": "/absolute/path/to/dxi-mcp-server/start_mcp_server_uv.sh",
      "env": {
        "DCT_API_KEY": "your-api-key-here",
        "DCT_BASE_URL": "https://your-dct-host.company.com",
        "DCT_VERIFY_SSL": "true"
      }
    }
  }
}

Note: VS Code, Eclipse, and IntelliJ all use the same configuration format (servers object).

Advanced Installation

For standalone command-line tool or contribute to development.

Most use the MCP Client Configuration above instead.

Setting Environment Variables

For standalone installation, to set the environment variables in your shell before running the server.

Linux/macOS

Use the export command to set variables for your current shell session. For improved security, avoid adding secrets like the API key to your shell's profile file.

Production Example:

export DCT_API_KEY="your-production-key"
export DCT_BASE_URL="https://dct-prod.company.com"
export DCT_VERIFY_SSL="true"
export DCT_LOG_LEVEL="INFO"

Development Example:

export DCT_API_KEY="your-development-key"
export DCT_BASE_URL="https://dct-dev.company.com"
export DCT_VERIFY_SSL="false"
export DCT_LOG_LEVEL="DEBUG"

Windows

Use the set command in Command Prompt or $env: in PowerShell for the current session. For improved security, avoid setting secrets like the API key permanently.

Command Prompt:

set DCT_API_KEY="your-production-key"
set DCT_BASE_URL="https://dct-prod.company.com"
set DCT_VERIFY_SSL="true"

PowerShell:

$env:DCT_API_KEY="your-production-key"
$env:DCT_BASE_URL="https://dct-prod.company.com"
$env:DCT_VERIFY_SSL="true"

Quick Start (Command-Line Tool)

Recommended method for users who want to use the server without modifying its code.

Prerequisites:

Python 3.11+
pip and git installed on your system
Environment variables configured in your shell. See above examples.

Install the server directly from GitHub using pip:

pip install git+https://github.com/delphix/dxi-mcp-server.git

# Verify the installation
dct-mcp-server --help

This makes the dct-mcp-server command available globally in your environment.

Developer Setup

Method for developers who want to modify the code or run it from a local clone.

Prerequisites:

Python 3.11+
git installed on your system
Environment variables configured in your shell. See above examples.

Steps:

Clone the repository:

git clone https://github.com/delphix/dxi-mcp-server.git
cd dxi-mcp-server

Set up the environment and install dependencies:

The included scripts handle environment setup automatically. We recommend using uv (which provides uvx) for the best performance:

Linux/macOS:
```
chmod +x start_mcp_server_uv.sh
./start_mcp_server_uv.sh
```
Windows:
```
start_mcp_server_windows_uv.bat
```
Note: If you prefer not to use uv, scripts for standard Python with venv are also provided (start_mcp_server_python.sh and start_mcp_server_windows_python.bat).

Connecting a Client to a Running Server

Once the server is running (either via the command-line tool or from the source), it will print the port it is listening on to the console (e.g., INFO: Uvicorn running on http://127.0.0.1:6790 (Press CTRL+C to quit)).

To connect your client, you only need to specify this port number. You do not need to provide environment variables in the client configuration, as the server already has them from your terminal session.

Example for Claude Desktop:

{
  "mcpServers": {
    "delphix-dct": {
      "port": 6790
    }
  }
}

Note: You can configure other MCP clients similarly by providing the port number. This method is ideal for development, as it allows you to restart the server without reconfiguring or restarting your client application. For troubleshooting, all log files can be found in the logs directory created in the project root.

Available Tools

The server provides specialized tools for interacting with different aspects of the Delphix DCT API:

Dataset Management Tools

search_data_connections - Find and filter database connections

Purpose: Discover database connections by platform, status, and capabilities
Parameters: filter_expression, limit, cursor, sort
Use cases: Connection discovery, status monitoring, platform inventory

search_dsources - Search for dSource objects (linked data sources)

Purpose: Find linked data sources with filtering and pagination
Parameters: filter_expression, limit, cursor, sort
Use cases: Data source management, capacity planning, source discovery

search_snapshots - Locate specific snapshots across datasets

Purpose: Find snapshots with time-based filtering
Parameters: filter_expression, limit, cursor, sort
Use cases: Point-in-time recovery, backup verification, timeline analysis

search_sources - Find source database objects and their configurations

Purpose: Discover source databases and their settings
Parameters: filter_expression, limit, cursor, sort
Use cases: Source inventory, configuration review, compliance checking

search_timeflows - Search timeline flows for data history

Purpose: Find timeline flows and recovery points
Parameters: filter_expression, limit, cursor, sort
Use cases: Data lineage, recovery planning, timeline management

search_vdb_groups - Locate virtual database groups

Purpose: Find VDB groups and their member databases
Parameters: filter_expression, limit, cursor, sort
Use cases: Group management, resource organization, bulk operations

search_vdbs - Search virtual databases

Purpose: Find virtual databases with status and environment filtering
Parameters: filter_expression, limit, cursor, sort
Use cases: VDB inventory, environment management, status monitoring

Environment Management Tools

search_environments - Find database environments

Purpose: Discover environments by type, status, and configuration
Parameters: filter_expression, limit, cursor, sort
Use cases: Environment discovery, capacity planning, status monitoring

Engine Administration Tools

search_engines - Locate Delphix engines

Purpose: Find engines and check their operational status
Parameters: filter_expression, limit, cursor, sort
Use cases: Engine monitoring, capacity management, health checking

Compliance & Security Tools

search_connectors - Find compliance connectors

Purpose: Discover connectors for data governance workflows
Parameters: filter_expression, limit, cursor, sort
Use cases: Compliance management, connector inventory, governance tracking

search_executions - Search compliance execution history

Purpose: Find compliance execution history and audit trails
Parameters: filter_expression, limit, cursor, sort
Use cases: Audit trail analysis, compliance reporting, execution monitoring

Job Monitoring Tools

search_jobs - Search job execution history

Purpose: Find jobs with status filtering and error details
Parameters: filter_expression, limit, cursor, sort
Use cases: Job monitoring, error analysis, performance tracking

Reporting & Analytics Tools

search_storage_capacity_data - Get storage capacity metrics

Purpose: Retrieve storage capacity and utilization data
Parameters: filter_expression, limit, cursor, sort
Use cases: Capacity planning, storage optimization, usage reporting

search_storage_savings_summary_report - Generate storage efficiency reports

Purpose: Create storage efficiency and compression reports
Parameters: filter_expression, limit, cursor, sort
Use cases: Cost analysis, efficiency reporting, savings tracking

search_virtualization_storage_summary_report - Create virtualization impact reports

Purpose: Generate virtualization impact and savings reports
Parameters: filter_expression, limit, cursor, sort
Use cases: ROI analysis, virtualization benefits, impact assessment

Common Tool Features

All tools support:

Advanced Filtering: Complex filter expressions using comparison operators (EQ, NE, GT, LT, CONTAINS, IN) and logical operators (AND, OR, NOT)
Flexible Pagination: Control result sets with limit and cursor parameters
Smart Sorting: Sort results by any available field in ascending or descending order
Comprehensive Search: Use the SEARCH operator to find items across multiple attributes
Error Handling: Detailed error responses with actionable troubleshooting information

Filter Expression Examples

# Find active Oracle databases
"filter_expression": "platform EQ 'oracle' AND status EQ 'ACTIVE'"

# Search for large datasets (> 100GB)
"filter_expression": "size GT 107374182400"

# Find resources with specific tags
"filter_expression": "tags CONTAINS 'production'"

# Complex logical expressions
"filter_expression": "NOT (status EQ 'INACTIVE') AND (platform IN ['oracle', 'postgresql'])"

Privacy & Telemetry

When IS_LOCAL_TELEMETRY_ENABLED is set to true, the server collects anonymous usage analytics to improve functionality and user experience.

What Data is Collected

Tool execution details: Tool name, execution status (success or failure), and session duration
User identifier: Operating system username (via getpass.getuser()) for usage analysis
Error context: Anonymized error types and frequencies (no sensitive data)
Performance metrics: Execution times and resource usage

What is NOT Collected

Sensitive data: No API keys, database content, or business data
Personal information: No personally identifiable information beyond OS username
DCT data: No data returned from DCT API calls
Network details: No IP addresses or network configurations

Data Storage & Privacy

Local only: Telemetry data is stored in the logs/sessions/ directory
No remote transmission: Data never leaves your machine
User control: Disable telemetry by setting IS_LOCAL_TELEMETRY_ENABLED="false"
Readable format: Logs use human-readable JSON

Sample Telemetry Entry

{
  "session_id": "abc123",
  "timestamp": "2025-12-05T10:30:00Z",
  "user": "developer",
  "tool": "get_datasets",
  "status": "success",
  "duration_ms": 245,
  "args_count": 3
}

Troubleshooting

Common Issues

Connection Errors

# Check DCT connectivity
curl -k -H "Authorization: Bearer $DCT_API_KEY" "$DCT_BASE_URL/v1/about"

# Verify SSL settings
export DCT_VERIFY_SSL="false"  # For self-signed certificates

Authentication Failures

# Verify API key is set
echo $DCT_API_KEY  # Should be your DCT API key (do NOT add 'apk' prefix)

# Check API key permissions in DCT admin console

Tool Generation Issues

# Enable debug logging
export DCT_LOG_LEVEL="DEBUG"

# Check DCT API accessibility
curl -k "$DCT_BASE_URL/v1/about"

MCP Client Connection Issues

# Test server startup
./start_mcp_server_python.sh

# Verify Python path
export PYTHONPATH=src
python -c "import dct_mcp_server; print('Import successful')"

Debug Mode

Enable comprehensive debugging:

export DCT_LOG_LEVEL="DEBUG"
export IS_LOCAL_TELEMETRY_ENABLED="true"
./start_mcp_server_python.sh 2>&1 | tee debug.log

Log Analysis

By default, all log files are generated in a logs directory. The location depends on how the server is started:

Local development: When you run the server from the cloned source code, the logs directory is created at the root of the project.
Client application: When an MCP client starts the server, the logs directory is typically created at the root of the workspace or project folder you have open in that client.

Check these logs for issues:

# Main application logs
tail -f logs/dct_mcp_server.log

# Session telemetry
ls -la logs/sessions/

# Startup logs
cat logs/mcp_server_setup_logfile.txt

"Server starting..." followed by "No such file or directory" or "command not found"

Cause: This happens when the command path in your MCP client's JSON configuration is incorrect. The client optimistically reports that it is "starting" the server, but then the operating system immediately fails because it cannot find the script at the specified location.
Solution: Ensure the command value is the absolute path to the correct startup script (e.g., start_mcp_server_uv.sh or start_mcp_server_python.sh). Verify that the file exists at that exact path and that it has execute permissions (chmod +x <script_name>).

Project Structure

dxi-mcp-server/
├── README.md                   # This file
├── LICENSE.md                  # MIT license
├── pyproject.toml              # Python project configuration
├── requirements.txt            # Dependencies (legacy format)
├── uv.lock                     # Locked dependencies (uv format)
├── start_mcp_server_*.{sh,bat} # Cross-platform startup scripts
├── logs/                       # Runtime logs and telemetry
│   ├── dct_mcp_server.log      # Main application logs
│   └── sessions/               # Telemetry session logs
└── src/
    └── dct_mcp_server/
        ├── main.py             # Application entry point
        ├── config/
        │   └── config.py       # Configuration management
        ├── core/
        │   ├── decorators.py   # Logging and telemetry decorators
        │   ├── exceptions.py   # Custom exception classes
        │   ├── logging.py      # Logging configuration
        │   └── session.py      # Session and telemetry management
        ├── dct_client/
        │   └── client.py       # DCT API HTTP client
        ├── tools/              # MCP tools for DCT endpoints
        │   ├── dataset_endpoints_tool.py
        │   ├── environment_endpoints_tool.py
        │   ├── engine_endpoints_tool.py
        │   ├── compliance_endpoints_tool.py
        │   ├── job_endpoints_tool.py
        │   └── reports_endpoints_tool.py
        └── icons/
            └── logo-delphixmcp-reg.png

License

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

Support & Contributing

Getting Help

Check the logs: Review logs/dct_mcp_server.log for error details.
Enable debug mode: Set DCT_LOG_LEVEL="DEBUG" for verbose output.
Search existing issues: Check GitHub Issues for similar problems.
Create a new issue: Provide DCT version, Python version, and error logs.

Community Resources

Issues: Report bugs and request features on GitHub Issues
Documentation: Full documentation available in the project wiki
Community support: - Community-driven support
Delphix DCT API documentation: Official API docs

Contributing

We welcome contributions! Please review our community documents:

Community Guidelines: An overview of how our community operates.
Code of Conduct: Our commitment to a respectful and inclusive environment.
Contributing Guidelines: The technical guide on how to contribute to this project.

When you are ready to submit a change, please use our Pull Request Template.

Enable your AI assistants to seamlessly manage your data infrastructure with Delphix DCT.

Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
.github		.github
src/dct_mcp_server		src/dct_mcp_server
.gitignore		.gitignore
.whitesource		.whitesource
LICENSE.md		LICENSE.md
README.md		README.md
pyproject.toml		pyproject.toml
requirements.txt		requirements.txt
start_mcp_server_python.sh		start_mcp_server_python.sh
start_mcp_server_uv.sh		start_mcp_server_uv.sh
start_mcp_server_windows_python.bat		start_mcp_server_windows_python.bat
start_mcp_server_windows_uv.bat		start_mcp_server_windows_uv.bat
uv.lock		uv.lock

License

delphix/dxi-mcp-server

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Delphix DCT API MCP Server

Table of Contents

Features

Quick Start

Videos

Environment Variables

MCP Client Configuration

Configuration Methods

Advanced Installation

Setting Environment Variables

Quick Start (Command-Line Tool)

Developer Setup

Connecting a Client to a Running Server

Available Tools

Dataset Management Tools

Environment Management Tools

Engine Administration Tools

Compliance & Security Tools

Job Monitoring Tools

Reporting & Analytics Tools

Common Tool Features

Filter Expression Examples

Privacy & Telemetry

What Data is Collected

What is NOT Collected

Data Storage & Privacy

Sample Telemetry Entry

Troubleshooting

Common Issues

Debug Mode

Log Analysis

"Server starting..." followed by "No such file or directory" or "command not found"

Project Structure

License

Support & Contributing

Getting Help

Community Resources

Contributing

About

Topics

Resources

License

Code of conduct

Contributing

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