
Greenlake Audit Logs Mcp
io.github.HewlettPackard由 GitHub 账号 HewlettPackard 发布v1.1.2更新于 Oct 24, 2026
HPE GreenLake audit-logs MCP Server
发布方自己的服务:audit.domains - Domain Valuation
概览
只读的 MCP 服务器,让 AI 助手通过平台 API 查询和分析 HPE GreenLake 审计日志。
- 可以做什么
- 查询和分析审计日志,可按类别、用户和时间戳筛选,追踪用户活动与系统事件
- 在动态模式下,通过三个通用元工具发现 API 端点、获取端点架构并执行调用
- 使用 OAuth2 客户端凭据登录 HPE GreenLake,令牌缓存在内存中并自动刷新
- 适用场景
- 适用于使用 HPE GreenLake 的场景:希望助手调查工作区内谁做了什么,或在对话中直接查看审计事件以回答安全与合规问题。
- 运行要求
- 以 Python 包形式在本地通过 stdio 运行(需 Python 3.10 或更高版本及 uv 包管理器)。需要一个 HPE GreenLake 工作区及 API 凭据,通过环境变量提供:GREENLAKE_API_BASE_URL、GREENLAKE_CLIENT_ID、GREENLAKE_CLIENT_SECRET 和 GREENLAKE_WORKSPACE_ID。需要能访问 GreenLake API 的网络;MCP_TOOL_MODE 用于选择静态或动态工具模式。
安装
在 SourceWeft 中
- 打开 控制台中的 Greenlake Audit Logs Mcp,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
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.
来源:README.md,提交 83dc9ca
工具
0版本历史
1- v1.1.2最新Sep 16, 2026
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