@gitskyflux
基本信息
MCP Server to interact with Google Cloud Tasks
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"cloudtasks-mcp": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@gitskyflux/cloudtasks-mcp",
"--client",
"claude"
]
}
}
}List all Cloud Tasks queues in a specified location
Get details of a specific Cloud Tasks queue
Pause a Cloud Tasks queue
Resume a paused Cloud Tasks queue
List tasks in a Cloud Tasks queue
Get details of a specific task in a Cloud Tasks queue
Delete a task from a Cloud Tasks queue
A Model Context Protocol (MCP) server for Google Cloud Tasks that enables interactions with Google Cloud Tasks queues and tasks. It is designed for use with AI assistants like Claude Desktop to manage task queues programmatically.
Install via Smithery (npx -y @smithery/cli install @gitskyflux/cloudtasks-mcp --client claude) or manually by building the project and adding a configuration entry to claude_desktop_config.json. Set the GOOGLE_CLOUD_LOCATION_PROJECTS environment variable with comma‑separated location:project-id pairs, and place corresponding service account JSON key files in a keys folder.
It acts as a bridge between AI assistants (via the MCP protocol) and Google Cloud Tasks, allowing you to list, get, pause, resume, list tasks, get task details, and delete tasks without leaving the chat interface.
The server runs on Node.js and requires service account JSON key files for authentication. It expects a `keys` folder with one JSON file per project named after the project ID (e.g., `keys/google-project-id1.json`). The service account must have appropriate Cloud Tasks permissions (e.g., `Cloud Tasks Admin`).
Set the `GOOGLE_CLOUD_LOCATION_PROJECTS` environment variable to a comma‑separated list of `location:project-id` pairs. The first pair becomes the default project. Example: `us-east1:my-project,us-central1:my-project2`.
The server uses standard I/O (stdio) as its transport, as configured in the Claude Desktop integration. Authentication is handled via the service account JSON key files placed in the `keys` folder; the server does not expose any network endpoints.
The README does not mention specific limits. However, the server relies on Google Cloud Tasks API quotas and permissions, and operations are limited to the queues and tasks accessible by the configured service accounts.
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