
Greenlake Audit Logs Mcp
io.github.HewlettPackard由 GitHub 帳號 HewlettPackard 發布v1.1.2更新於 Oct 24, 2026
HPE GreenLake audit-logs MCP Server
發布方自己的服務:audit.domains - Domain Valuation
概覽
唯讀的 MCP 伺服器,讓 AI 助理透過平台 API 查詢與分析 HPE GreenLake 稽核日誌。
- 可以做什麼
- 查詢與分析稽核日誌,可依類別、使用者與時間戳篩選,追蹤使用者活動與系統事件
- 在動態模式下,透過三個通用中繼工具探索 API 端點、取得端點結構描述並執行呼叫
- 以 OAuth2 用戶端憑證登入 HPE GreenLake,權杖僅快取於記憶體並自動更新
- 適用情境
- 適用於使用 HPE GreenLake 的情境:想讓助理調查工作區內誰做了什麼,或在對話中直接檢視稽核事件以回答安全與合規問題。
- 執行需求
- 以 Python 套件形式在本機透過 stdio 執行(需 Python 3.10 以上與 uv 套件管理工具)。需要 HPE GreenLake 工作區與 API 憑證,透過環境變數提供:GREENLAKE_API_BASE_URL、GREENLAKE_CLIENT_ID、GREENLAKE_CLIENT_SECRET 與 GREENLAKE_WORKSPACE_ID。需要可連線 GreenLake API 的網路;MCP_TOOL_MODE 可選擇靜態或動態工具模式。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Greenlake Audit Logs Mcp,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
HPE GreenLake MCP Servers
[License] [Python Versions] [Code style: ruff] [Security Policy] [CI Status]
A collection of Model Context Protocol (MCP) servers that enable AI assistants to interact with HPE GreenLake platform services.
Table of Contents
- What is the Model Context Protocol?
- What's in this Repository?
- Available MCP Servers
- Quick Start
- MCP Client Configuration
- Tool Modes
- Architecture Overview
- Security Considerations
- Troubleshooting
- Getting Help
- Resources
- License
What is the Model Context Protocol?
The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.
What's in this Repository?
This repository contains production-ready MCP servers for HPE GreenLake platform services. Each server provides AI assistants with secure, read-only access to specific GreenLake APIs, enabling natural language interactions with your HPE infrastructure.
Key Features
- Standardized Architecture: All servers follow consistent patterns for authentication, configuration, and error handling
- OAuth2 Authentication: Secure access using HPE GreenLake workspace credentials with automatic token management
- Dual Tool Modes: Each server supports both static (individual tools per endpoint) and dynamic (meta-tools) operation modes
- Type-Safe: Built with Pydantic models for runtime validation and type safety
- Production Ready: Comprehensive logging, error handling, and Docker support
- Well Tested: Extensive unit and integration test coverage
Available MCP Servers
Quick Start
Prerequisites
- Python 3.10 or higher
- uv package manager
- HPE GreenLake workspace with API credentials
Configuration
All servers require the following HPE GreenLake credentials:
Running a Server
MCP Client Configuration
Claude Desktop
Add servers to your claude_desktop_config.json:
Other MCP Clients
These servers use the standard stdio transport and work with any MCP-compatible client. See individual server READMEs for specific configuration examples.
Tool Modes
All servers support two operation modes that can be switched at runtime using the MCP_TOOL_MODE environment variable:
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 and focused workflows
Dynamic Mode
- Meta-tools: 3 generic tools that can handle any API endpoint
list_endpoints- Discover available API endpointsget_endpoint_schema- Get detailed schema informationinvoke_dynamic_tool- Execute API calls with runtime validation
- Memory efficient: Lower overhead for large APIs
- Best for: Large APIs with many endpoints
Compatibility Matrix
Architecture Overview
High-Level Architecture
Request Flow
- Client Request: MCP client sends tool invocation via JSON-RPC over stdio
- Authentication: Server authenticates with HPE GreenLake using OAuth2 (tokens cached and auto-refreshed)
- API Call: Server makes authenticated HTTPS request to GreenLake API
- Response: Server processes response and returns data to client via MCP protocol
Shared Components
All servers share a common architecture:
Authentication
All servers use OAuth2 client credentials flow with automatic token management:
- Tokens are cached and automatically refreshed
- Thread-safe token management
- Configurable retry logic with exponential backoff
Logging
Servers use structured logging with MCP protocol compliance:
- stderr: Diagnostic logs (controlled by
GREENLAKE_LOG_LEVEL) - File logging: Optional detailed logging to
~/.hpe/mcp-logs/ - stdout: Reserved for JSON-RPC messages only
Security Considerations
- Read-Only Access: All servers provide read-only API access by design
- Credential Management: Never commit credentials to version control
- Token Security: OAuth2 tokens are cached in memory only
- Workspace Isolation: Operations are scoped to the configured workspace
- HTTPS Only: All API communications use TLS encryption
Troubleshooting
Common Issues
Server won't start:
- Verify all required environment variables are set
- Check that
uvis installed and dependencies are synced - Review stderr output for configuration errors
Authentication failures:
- Verify client credentials are valid for your workspace
- Ensure
GREENLAKE_WORKSPACE_IDmatches your credential scope - Check network connectivity to GreenLake APIs
MCP client connection issues:
- Verify the
cwdpath in client configuration is correct - Check that the server starts successfully when run manually
- Review client logs for specific error messages
Debug Logging
Enable detailed logging for troubleshooting:
Log files are written to: ~/.hpe/mcp-logs/{service-name}/
Getting Help
GitHub Issues
The primary support channel for this project is GitHub Issues. When reporting an issue, please include:
- Environment details: OS, Python version,
uvversion - Server name: Which MCP server you're using (audit-logs, devices, etc.)
- Error messages: Complete error output with stack traces
- Configuration: Relevant environment variable settings (DO NOT include credentials)
- Steps to reproduce: Detailed description of how to reproduce the issue
Before Opening an Issue
- Check existing issues: Search open and closed issues
- Review troubleshooting: Check the Troubleshooting section above
- Enable debug logging: Run with
GREENLAKE_LOG_LEVEL=DEBUGandGREENLAKE_FILE_LOGGING=trueto gather detailed logs - Test authentication: Verify your credentials work with the GreenLake APIs directly
Issue Types
- Bug Report: For unexpected behavior, errors, or crashes
- Feature Request: For suggesting new capabilities or improvements
- Question: For clarification on usage, configuration, or architecture
- Documentation: For reporting documentation issues or suggesting improvements
Resources
License
This project is licensed under the Apache 2.0 - see the LICENSE file for details.
來源:README.md,提交 83dc9ca
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0版本歷史
1- v1.1.2最新Sep 16, 2026
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