CloudBase AI Toolkit

AI writes the code. CloudBase runs the backend.

The CloudBase integration layer for AI coding tools: Plugin installs the stack, Skills steer how code is written, MCP operates databases, functions, storage, and deploys from chat.

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Recent updates

v2.25.x (2026-07)

• CloudRun / Gateway: VPC guidance when using TCP databases; Domain/Route with upstreamResourceType and path transmission

• Plugin: easier install via Open Plugin / marketplace packaging

Releases · Star · Watch → Releases

Related MCP server: CreateOS MCP

What it is

AI IDEs (Cursor, Claude Code, Codex, CodeBuddy, and others) are strong at generating code. What usually blocks you is the backend: schemas, permissions, functions, storage, environments, and release.

CloudBase is Tencent Cloud’s AI-native all-in-one backend (database, storage, auth, cloud functions, Cloud Run, and more). This repo is the Toolkit that connects that backend to AI tools:

This repository ships the npm package @cloudbase/cloudbase-mcp, Skills, and AI plugins.

You still need your own CloudBase environment, and you should confirm sensitive actions the AI proposes. The Toolkit provides capability and path—not judgment.

Related repositories

Publishing and sync repos live under TencentCloudBase. Directly related to this Toolkit:

Prefer Plugin for the full stack; Skills alone when you only need knowledge constraints. For marketplace IDEs use this repo—do not also run npx plugins add on the same tool.

Quick start

Pick one default path for your tool.

Plugin

npx plugins add TencentCloudBase/cloudbase-plugin

Details and IDE differences: AI plugin docs.

MCP only

{
  "mcpServers": {
    "cloudbase": {
      "command": "npx",
      "args": ["@cloudbase/cloudbase-mcp@latest"]
    }
  }
}

Hosted HTTP, self-hosted Cloud Mode, and plugin scoping: Install & connect.

First prompts

Login to CloudBase

Use CloudBase Skills to build a todo app with login, database and permissions, then deploy

Skills shape structure and practice; MCP handles environment and resources. You should be able to verify data and APIs in your own environment—not only get local source files.

Supported AI IDEs

Full setup: IDE guides.

Capabilities

After setup, the AI can do typical backend work in your environment (confirm critical steps):

• Database: PostgreSQL and document DB, data models, CRUD, permissions and security rules

• Compute: author, deploy, invoke, and debug cloud functions / Cloud Run

• Auth & storage: login methods, object storage, permission linkage with data

• Release & ops: static hosting / Mini Program publish; inspect logs and redeploy

Fits Web, WeChat Mini Programs, and backend services. Platform overview: CloudBase docs.

Evaluation

Under controlled conditions, the same Todo application brief and frontend scaffold were used to compare two backend paths: a traditional cloud VM (self-managed runtime, process, and network exposure) and CloudBase (managed database, anonymous auth, and related backend services). An AI agent performed end-to-end development and verification. Given the model and task setup, the CloudBase path was more favorable in completion latency, token usage, and tool-call count. These outcomes are conditioned on the model, agent framework, and task definition, and should not be generalized beyond that scope.

Methods, data, and limits: Same-task evaluation: cloud VM vs CloudBase

Install & connect

Prerequisites

• Node.js v18.15.0+

• A CloudBase environment

• An AI tool that supports Plugin / Skills / MCP

Setup options

1. Plugin (when the tool supports it)
   npx plugins add TencentCloudBase/cloudbase-plugin

2. CloudBase AI CLI
   npm i -g @cloudbase/cli && tcb ai

3. Manual MCP (write the IDE config file)

{
  "mcpServers": {
    "cloudbase": {
      "command": "npx",
      "args": ["@cloudbase/cloudbase-mcp@latest"]
    }
  }
}

{
  "mcpServers": {
    "cloudbase": {
      "command": "npx",
      "args": ["@cloudbase/cloudbase-mcp@latest"]
    }
  }
}

CloudBase is built in (MCP / Skills); manual config is usually unnecessary.

Others: IDE setup guide.

MCP connection modes

Local (default): npx on your machine—full features, including local filesystem upload/templates.

Hosted: IDE connects over HTTP to Tencent Cloud MCP; no local Node. Some local-file features are unavailable.

{
  "mcpServers": {
    "cloudbase": {
      "type": "http",
      "url": "https://tcb-api.cloud.tencent.com/mcp/v1?env_id=<env_id>",
      "headers": {
        "X-TencentCloud-SecretId": "<Tencent Cloud Secret ID>",
        "X-TencentCloud-SecretKey": "<Tencent Cloud Secret Key>"
      }
    }
  }
}

Hosted URLs can use enable_plugins / disable_plugins. Canonical names live in mcp/src/server.ts.

Self-hosted Cloud Mode: set CLOUDBASE_MCP_CLOUD_MODE=true (or MCP_CLOUD_MODE=true) so local file and process tools are disabled for remote callers.

Example

Online Gomoku: describe the need; get Web + cloud database / realtime and deploy.
Demo: Gomoku · More: tutorials

Docs

• MCP tools (tools.json)

• Getting started

• IDE setup

• AI plugins

• Templates

• FAQ

FAQ

Those focus on shipping frontends or containers. CloudBase provides backend building blocks (database, auth, functions). The Toolkit lets AI tools use them in chat. Deploy is only part of the path.

Yes. Any tool that can configure an MCP Server or install the matching Plugin / Skills works—including Claude Code, Gemini CLI, OpenCode. Support list

Deploy targets your own CloudBase environment. In local mode MCP runs on your machine; code need not leave until you deploy. Cloud traffic uses HTTPS.

Local npx is equivalent to running tools yourself. For remote hosts, set CLOUDBASE_MCP_CLOUD_MODE=true to disable local file/process tools. Tencent Cloud hosted HTTP includes this protection.

The Toolkit (including MCP) is open source under MIT. CloudBase has free quotas; usage beyond that is billed—see billing.

Confirm an environment exists and is healthy in the console, then login again and pick the right one.

Community

Activity

Contributors

MIT · TencentCloudBase