Skip to main content

Documentation Index

Fetch the complete documentation index at: https://gcore.com/docs/llms.txt

Use this file to discover all available pages before exploring further.

Prerequisites and server installation common to all AI clients. For client-specific configuration, see Connect Claude Code or Connect Cursor IDE.

​
Prerequisites

Install uv Gcore MCP Server runs via uvx, which is part of the uv package manager. 
curl -LsSf https://astral.sh/uv/install.sh | sh
Verify the installation: 
uv --version
Create a Gcore API token Create an API token with permissions matching the products to be used. See API token permissions for required roles per product.
The API token is displayed once and cannot be retrieved later. Store it securely and do not commit it to version control.

​
Install the server

uvx runs the server in a temporary environment without installing it permanently. The AI client handles this automatically using the uvx command in its configuration—no manual step is needed.To verify the server starts correctly, run it directly:
uvx --from "gcore-mcp-server@git+https://github.com/G-Core/gcore-mcp-server.git" gcore-mcp-server
Pin a specific version by appending the tag:
uvx --from "gcore-mcp-server@git+https://github.com/G-Core/gcore-mcp-server.git@v0.1.1" gcore-mcp-server
If the AI client shows “Failed to connect to MCP server”, verify that uv is installed (uv --version) and test the uvx command directly from the terminal. A missing comma or bracket in the config file also prevents loading.

​
Environment variables

VariableRequiredDescription
GCORE_API_KEYYesAPI token for authentication
GCORE_TOOLSNoTool filter pattern — controls which tools are loaded
GCORE_CLOUD_PROJECT_IDNoDefault project ID for Cloud operations
GCORE_CLOUD_REGION_IDNoDefault region ID for Cloud operations
Requests that return “401 Unauthorized” indicate an invalid or expired API token. Verify the token in the Gcore Customer Portal and check that it has permissions for the requested product.

​
Configure Cloud defaults

Cloud tools require project_id and region_id for most operations. Setting defaults avoids specifying them in every request. To find project and region IDs, ask the AI client: 
List my Cloud projects

List available Cloud regions
Or navigate to Cloud > Projects in the Gcore Customer Portal and check the URL for region IDs. Once the IDs are known, add them to the env section of the AI client configuration: 
{
  "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": "your-api-key",
        "GCORE_TOOLS": "cloud.*",
        "GCORE_CLOUD_PROJECT_ID": "1186668",
        "GCORE_CLOUD_REGION_ID": "76"
      }
    }
  }
}
With defaults set, requests like “Create a VM with 2 vCPUs” use the specified project and region automatically.
If Cloud requests return errors about a missing project or region, add GCORE_CLOUD_PROJECT_ID and GCORE_CLOUD_REGION_ID to the env section, or specify them inline: “List VMs in project 1186668, region Luxembourg”. Requests that return “429 Too Many Requests” indicate rate limiting—wait 60 seconds before retrying.