What toolsets does Gcore Cloud Mcp Server provide?
It provides nine predefined toolsets: management, instances, volumes, networks, baremetal, gpu_baremetal, cleanup, list, and more.
@G-Core
基本信息
Gcore MCP Server makes your AI assistant:
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"gcore-mcp-server": {
"command": "uvx",
"args": [
"--from",
"gcore-mcp-server@git+https://github.com/G-Core/gcore-mcp-server.git",
"gcore-mcp-server"
],
"env": {
"GCORE_API_KEY": "24590$.....234",
"GCORE_TOOLS": "instances,management,cloud.gpu_baremetal_clusters.*"
}
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
Gcore Cloud Mcp Server is an MCP server that exposes Gcore’s cloud API tools to LLM assistants, allowing them to manage cloud resources through predefined tool sets. It is intended for DevOps and cloud automation workflows.
Install with uv tool install "gcore-mcp-server@git+https://github.com/G-Core/gcore-mcp-server.git" and run gcore-mcp-server. Configure resource categories via the GCORE_TOOLS environment variable (e.g., management,instances or wildcard patterns like cloud.instances.*). Point your LLM client at the HTTP endpoint or use stdio mode to start issuing MCP requests.
GCORE_TOOLS environment variable.It provides nine predefined toolsets: management, instances, volumes, networks, baremetal, gpu_baremetal, cleanup, list, and more.
Set the `GCORE_TOOLS` environment variable with a comma-separated list of toolset names or wildcard patterns (e.g., `management,instances` or `cloud.instances.*`).
HTTP and stdio modes are supported. HTTP defaults to `management,instances`, and stdio defaults to `management`.
Install using `uv tool install "gcore-mcp-server@git+https://github.com/G-Core/gcore-mcp-server.git"` and then run `gcore-mcp-server`.
Yes, you can use MCP Inspector (`npx @modelcontextprotocol/inspector`) to explore tools, test calls, and monitor LLM-server traffic in real time.
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