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Gcore Cloud Mcp Server

Created By
Gcore5 months ago
Gcore MCP Server makes your AI assistant: Discover your tenant/project hierarchy, quotas, and permissions Invoke Gcore CLI/API methods on your behalf Return structured JSON results that the model can render as tables, charts, or plain text This makes it possible to “chat” with your cloud: ask for capacity checks, spin up instances, manage networks, or tear down stacks—all via natural-language prompts .
Content

Configuration & Usage

Tool Selection

Define which resource categories your MCP server should expose by setting the GCORE_TOOLS environment variable. You can pick from predefined toolsets (e.g. instances,management) or use wildcard patterns ( e.g. cloud.instances.*,waap.* ) to fine-tune exactly which API calls are available.

Transport Modes

  • HTTP mode defaults to management,instances
  • stdio mode defaults to management

Running the Server

uv tool install "gcore-mcp-server@git+https://github.com/G-Core/gcore-mcp-server.git"
gcore-mcp-server

Then point your LLM client at the server’s HTTP endpoint (or use stdio) and begin issuing MCP requests.

MCP Inspector (Optional)

For developing and debugging, use the MCP Inspector web UI (npx @modelcontextprotocol/inspector) to explore available tools, test calls, and watch the LLM - server traffic in real time.

Available Toolsets & Core Functionality

The server ships with nine predefined toolsets covering common cloud workflows. Each toolset bundles a logical group of operations:

  • management - Account, project, role and permission management
  • instances - VM lifecycle: create, stop, reboot, resize, snapshot
  • volumes - Block storage: create, attach/detach, snapshot, resize
  • networks - VPCs, subnets, security groups, load balancers, VPNs
  • baremetal - Provision and manage dedicated physical servers
  • gpu_baremetal - Spin up and orchestrate GPU clusters for HPC and rendering
  • cleanup - Bulk-delete resources, cleanup stale objects, teardown stacks
  • list - Read-only inventory: list model instances and metadata

You can combine these toolsets (or mix in custom patterns) to tailor your MCP surface for any task—whether it’s spinning up a GPU cluster, auditing costs, or tearing down test environments.

With this foundation, Gcore MCP Server lets your LLM assistant act as a 24/7 DevOps partner, automating everything from core account setup to advanced AI/ML inference deployments.

Server Config

{
  "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.*"
      }
    }
  }
}
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