The CloudBase integration layer for AI coding tools: Plugin installs the stack, Skills steer how code is written, MCP operates databases, functions
If you already use Cloudbase Ai Toolkit, the cloudbase ai toolkit mcp server is the piece that lets your assistant work with it directly. 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.
The toolset is worth reading before you wire it up, because it tells you what the integration is really for:
Plugin — easier install via Open Plugin / marketplace packagingDatabase — PostgreSQL and document DB, data models, CRUD, permissions and security rulesCompute — author, deploy, invoke, and debug cloud functions / Cloud RunPiece — RoleMCP — Login, query and change data, manage functions and hosting, read logs—from the conversationRepository — ContentsScenario — SuggestionPersonal — Local npxDocs — docs.cloudbase.netIssues — GitHub IssuesReleases — [Changelog][changelog]Evaluation — Under controlled conditions, the same Todo application brief and frontend scaffold were used to compare two backend paths: a traditional cloud VMBecause this one is hosted, setup is mostly authentication — you point your client at the endpoint and approve access. Nothing runs on your machine, so there is no runtime to keep patched.
Among the developer tooling options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Cloudbase Ai Toolkit's toolset — Plugin, Database, Compute and 10 more — is a fair guide to whether it matches your workflow. It is maintained by tencentcloudbase; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| Plugin | easier install via Open Plugin / marketplace packaging |
| Database | PostgreSQL and document DB, data models, CRUD, permissions and security rules |
| Compute | author, deploy, invoke, and debug cloud functions / Cloud Run |
| Piece | Role |
| MCP | Login, query and change data, manage functions and hosting, read logs—from the conversation |
| Repository | Contents |
| Scenario | Suggestion |
| Personal | Local npx |
| Docs | [docs.cloudbase.net](https://docs.cloudbase.net/) |
| Issues | [GitHub Issues](https://github.com/TencentCloudBase/CloudBase-AI-Toolkit/issues) |
| Releases | [Changelog][changelog] |
| 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 (manag |
| Prerequisites | The Prerequisites tool exposed by this server. |
{
"mcpServers": {
"cloudbase": {
"command": "npx",
"args": ["@cloudbase/cloudbase-mcp@latest"]
}
}
}Configuration as documented by the project. Restart the client after saving.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Microsoft's official browser automation server — drive a real browser through the accessibility tree, no screenshots needed.
GitHub's official server — repos, issues, pull requests, Actions and code security, straight from your assistant.
Issue tracking at the speed of conversation — Linear's official hosted server with OAuth and zero install.
Local repository surgery — status, diffs, commits, branches and history for any repo on disk.
Timezone sanity for AI — current time anywhere and correct conversions, without the model doing date math.