greenlake-workspaces-mcp 1.1.0

HPE GreenLake workspaces MCP Server

workspaces MCP Server

HPE GreenLake workspaces MCP Server provides read-only access to the HPE GreenLake workspaces APIs through the Model Context Protocol.

Overview

This MCP server enables AI assistants and development tools to interact with HPE GreenLake workspaces programmatically. It follows the standardized MCP server architecture with shared authentication components and HTTP client adapters.

Key Features

• Read-only API access to workspaces endpoints
• Shared authentication using OAuth2 with automatic token management
• Standardized architecture following HPE GreenLake MCP patterns
• Type-safe implementations using Pydantic models
• Comprehensive logging and error handling

Quick Start

Prerequisites

• Python 3.10 or higher
• uv package manager
• HPE GreenLake workspace with API credentials

Installation

From PyPI (recommended):

pip install greenlake-workspaces-mcp

After installation, run the server with:

python -m greenlake_workspaces_mcp

Configuration

Set the following environment variables:

Variable	Required	Description	Example
GREENLAKE_API_BASE_URL	Yes	Base URL for GreenLake APIs	https://global.api.greenlake.hpe.com
GREENLAKE_CLIENT_ID	Yes	OAuth2 client ID	your-client-id
GREENLAKE_CLIENT_SECRET	Yes	OAuth2 client secret	your-client-secret
GREENLAKE_WORKSPACE_ID	Yes	Workspace identifier (token issuer auto-generated from this)	your-workspace-id
MCP_TOOL_MODE	No	Tool operation mode (see Tool Modes section)	static (default) or dynamic
GREENLAKE_LOG_LEVEL	No	Logging level for stderr output	ERROR (default), WARNING, INFO, DEBUG
GREENLAKE_FILE_LOGGING	No	Enable file logging to disk	false (default) or true

Logging

This MCP server uses loguru for structured logging with strict MCP protocol compliance.

Log Destinations

stderr (Default):

• All diagnostic logs go to stderr (MCP protocol requirement)
• Controlled by GREENLAKE_LOG_LEVEL (default: ERROR)
• stdout is reserved exclusively for JSON-RPC messages

File logging (Optional):

• Enable with GREENLAKE_FILE_LOGGING=true
• Logs written to: ~/.hpe/mcp-logs/workspaces/workspaces-mcp.log
• Features:
  • Automatic rotation at 10 MB
  • 7-day retention policy
  • Always logs at DEBUG level for comprehensive diagnostics
  • Includes detailed context (module, function, line number)

Configuration Examples

Production (minimal logging):

export GREENLAKE_LOG_LEVEL=ERROR
# File logging disabled by default

Development (verbose logging):

export GREENLAKE_LOG_LEVEL=DEBUG
export GREENLAKE_FILE_LOGGING=true

Debugging specific issues:

export GREENLAKE_LOG_LEVEL=INFO
export GREENLAKE_FILE_LOGGING=true
# Check logs at: ~/.hpe/mcp-logs/workspaces/

Log Filtering

The server automatically filters noisy third-party library logs:

• httpx, httpcore, urllib3, asyncio are limited to WARNING level and above
• This preserves important error messages (connection failures, timeouts, SSL issues)
• While suppressing verbose DEBUG/INFO output (connection pooling, retries)

Tool Modes

This MCP server supports two different tool operation modes that can be switched at runtime:

Static Mode (Default)

• Individual tools: Each API endpoint becomes a dedicated MCP tool
• Type-safe: Explicit tool definitions with compile-time validation
• Discoverable: Tools appear individually in MCP client interfaces
• Best for: Smaller APIs with focused functionality

Dynamic Mode

• Meta-tools: 3 generic tools that can handle any API endpoint
• Runtime discovery: Endpoints are discovered and validated at runtime
• Memory efficient: Lower overhead for large APIs
• Best for: Large APIs with many endpoints

Tools available in dynamic mode:

• list_endpoints - Discover available API endpoints with optional filtering
• get_endpoint_schema - Get detailed schema information for specific endpoints
• invoke_dynamic_tool - Execute API calls with runtime parameter validation

Switching Modes

Configure the MCP_TOOL_MODE environment variable in your MCP client configuration:

{
  "servers": {
    "workspaces": {
      "env": {
        "MCP_TOOL_MODE": "static"  // or "dynamic"
      }
    }
  }
}

• static - Individual tools per endpoint (default)
• dynamic - 3 generic meta-tools for all endpoints

MCP Client Configuration

VS Code

Add to your .vscode/mcp.json:

Using PyPI package:

{
  "servers": {
    "workspaces": {
      "type": "stdio",
      "command": "python",
      "args": ["-m", "greenlake_workspaces_mcp"],
      "env": {
        "GREENLAKE_API_BASE_URL": "https://global.api.greenlake.hpe.com",
        "GREENLAKE_CLIENT_ID": "your-client-id",
        "GREENLAKE_CLIENT_SECRET": "your-client-secret",
        "GREENLAKE_WORKSPACE_ID": "your-workspace-id",
        "MCP_TOOL_MODE": "static",
        "GREENLAKE_LOG_LEVEL": "INFO",
        "GREENLAKE_FILE_LOGGING": "false"
      }
    }
  }
}

Claude Desktop

Add to your claude_desktop_config.json:

Using PyPI package:

{
  "mcpServers": {
    "workspaces": {
      "command": "python",
      "args": ["-m", "greenlake_workspaces_mcp"],
      "env": {
        "GREENLAKE_API_BASE_URL": "https://global.api.greenlake.hpe.com",
        "GREENLAKE_CLIENT_ID": "your-client-id",
        "GREENLAKE_CLIENT_SECRET": "your-client-secret",
        "GREENLAKE_WORKSPACE_ID": "your-workspace-id",
        "MCP_TOOL_MODE": "static",
        "GREENLAKE_LOG_LEVEL": "INFO",
        "GREENLAKE_FILE_LOGGING": "false"
      }
    }
  }
}

Available Tools

This server provides the following MCP tools:

get_workspace_workspaces_v1_workspaces_workspaceid_get

• Description: Retrieve basic workspace information for a provided workspace identifier.

• Method: GET /workspaces/v1/workspaces/{workspaceId}

• Parameters:

  • workspaceId (str, required):
    The unique identifier of the workspace.

Example: 7600415a-8876-5722-9f3c-b0fd11112283

get_workspace_detailed_info_workspaces_v1_workspaces_wo_5c14f2bc

• Description: Retrieve detailed workspace information.

• Method: GET /workspaces/v1/workspaces/{workspaceId}/contact

• Parameters:

  • workspaceId (str, required):
    The unique identifier of the workspace.

Example: 7600415a-8876-5722-9f3c-b0fd11112283

Typical Use Cases

This MCP server enables AI assistants to answer natural language questions about your HPE GreenLake workspaces resources. Here are some example queries you can try:

Workspace Information:

• "Get details for workspace XYZ"
• "Show me workspace configurations"

These are just examples - you can ask questions in your own words, and the AI assistant will use the appropriate MCP tools to retrieve the information from HPE GreenLake.

API Coverage

This MCP server implements read-only access to the following workspaces API endpoints:

• GET /workspaces/v1/workspaces/{workspaceId} - Retrieve basic workspace information for a provided workspace identifier.
• GET /workspaces/v1/workspaces/{workspaceId}/contact - Retrieve detailed workspace information.

Development

Commands

make help          # Show available commands
make install       # Install dependencies
make test          # Run tests
make clean         # Clean build artifacts

Project Structure

workspaces/
├── pyproject.toml          # Dependencies and configuration
├── README.md               # This file
├── Makefile                # Development commands
├── greenlake_workspaces_mcp/           # Python package
│   ├── __init__.py
│   ├── __main__.py         # Entry point
│   ├── _version.py         # Version constants
│   ├── auth/               # Authentication components
│   │   ├── __init__.py
│   │   ├── oauth2_provider.py  # OAuth2 client credentials
│   │   └── token_manager.py    # Token lifecycle management
│   ├── config/             # Configuration management
│   │   ├── __init__.py
│   │   ├── logging.py      # Logging configuration
│   │   └── settings.py     # Application settings
│   ├── models/             # Data models
│   │   ├── __init__.py
│   │   └── base.py         # Base model classes
│   ├── server/             # MCP server implementation
│   │   ├── __init__.py
│   │   ├── app.py          # Application factory
│   │   ├── fastmcp_instance.py # FastMCP singleton
│   │   └── mcp_server.py   # MCP server core
│   ├── tools/              # MCP tools
│   │   ├── __init__.py
│   │   ├── base.py         # Base tool class
│   │   ├── registry.py     # Tool registration
│   │   └── implementations/
│   │       └── *.py        # Tool implementations
│   └── utils/              # Utility modules
│       ├── __init__.py
│       └── http_client.py  # HTTP client utilities
└── tests/                  # Test suite
    ├── conftest.py         # Shared fixtures
    ├── shared/
    │   └── http.py         # Testing helpers
    ├── unit/
    │   └── test_*.py       # Unit tests
    └── integration/
        └── test_live_tools.py

Adding New Tools

1. Create a new tool file in tools/implementations/
2. Inherit from BaseTool and implement required methods
3. Add the tool to tools/registry.py
4. Write tests in tests/
5. Update this README

Testing

The test suite reads credentials from environment variables. Export the following variables before running integration tests:

export GREENLAKE_CLIENT_ID=your-client-id
export GREENLAKE_CLIENT_SECRET=your-client-secret
export GREENLAKE_WORKSPACE_ID=your-workspace-id
export GREENLAKE_API_BASE_URL=https://global.api.greenlake.hpe.com

Run the full test suite (unit + integration when credentials are present):

make test

Run unit-only checks:

make test-unit

Integration smoke tests require the variables above plus any tool arguments (MCP_TEST_WORKSPACES_<PARAM_NAME>):

make test-integration

The generated suite provides:

• Unit tests for tools, server wiring, and models
• Shared fixtures and helpers for deterministic behaviour
• Integration tests guarded by environment variable checks
• Coverage reporting within the unit suite

Troubleshooting

Common Issues

Server won't start:

• Verify environment variables are set

• Check that the package is installed: pip show greenlake-workspaces-mcp

• Review log output for specific errors

Authentication failures:

• Verify client credentials are valid
• Check workspace ID is correct
• Ensure network connectivity to GreenLake

Tool execution errors:

• Check API endpoint availability
• Verify request parameters
• Review error logs for details

Contributing

1. Fork the repository
2. Create a feature branch
3. Implement changes following project standards
4. Add tests for new functionality
5. Submit a pull request

License

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