@tsdevstack/cli-mcp

@tsdevstack/cli-mcp

MCP server plugin for the tsdevstack CLI, enabling AI agents to manage infrastructure, deployment, and project state with 54 tools and 12 resources.

Category
访问服务器

README

@tsdevstack/cli-mcp

MCP (Model Context Protocol) server plugin for the tsdevstack CLI. Exposes 54 tools and 12 resources so AI agents like Claude can understand and assist you with the framework, the infrastructure, deployment flows and querying the project state.

Features

  • 54 MCP Tools — 13 read-only queries + 41 actions covering the full tsdevstack CLI surface
  • 12 MCP Resources — project state, secrets context, Kong routes, and framework guides
  • Stdio Transport — connects via stdin/stdout for IDE and agent integration
  • Zod Validation — all tool inputs validated with schemas
  • MCP Annotations — tools include readOnlyHint, destructiveHint, and idempotentHint metadata

Installation

npm install @tsdevstack/cli-mcp

Requires tsdevstack as a peer dependency.

Usage

As a CLI plugin

The MCP server registers as a plugin with the tsdevstack CLI:

import { initContext, registerMcpPlugin } from '@tsdevstack/cli-mcp';

// Initialize with CLI plugin context
initContext(pluginContext);

// Register the mcp:serve command
registerMcpPlugin(program);

Starting the server

npx tsdevstack mcp:serve

This starts the MCP server over stdio transport, ready for AI agent connections.

Claude Code integration

Add to your .mcp.json:

{
  "mcpServers": {
    "tsdevstack": {
      "command": "npx",
      "args": ["tsdevstack", "mcp:serve"]
    }
  }
}

Tools

Query tools (read-only)

Tool Description
list_services List all services with types and ports
list_environments List configured cloud environments
get_project_config Full project configuration
get_infrastructure_config Per-environment infrastructure settings
get_service_status Cloud resource status for a service
list_deployed_services All deployed services in an environment
list_secrets Secret names in cloud (not values)
diff_secrets Compare local vs cloud secrets
get_secret Get a single secret value
list_schedulers Scheduled jobs and status
plan_db_migrate Preview pending database migrations
infra_plan Terraform plan preview
infra_status Infrastructure sync status

Action tools — local

Tool Description
sync Regenerate all local config
generate_secrets Regenerate local secrets files
generate_kong Regenerate Kong gateway config
generate_docker_compose Regenerate docker-compose.yml
add_service Add a new service (nestjs, nextjs, spa)
remove_service Remove a service from the project
generate_client Generate TypeScript HTTP client from OpenAPI
add_bucket_storage Add an object storage bucket
remove_bucket_storage Remove an object storage bucket
add_messaging_topic Add a messaging topic to config
remove_messaging_topic Remove a messaging topic from config
update_messaging_topic Update publishers/subscribers for a topic
register_detached_worker Register a detached worker in config
unregister_detached_worker Remove a worker from config

Action tools — cloud

Tool Description
cloud_secrets_push Push secrets to cloud
cloud_secrets_set Set a single cloud secret
cloud_secrets_remove Remove a cloud secret
infra_deploy Full infrastructure deployment
deploy_services Deploy code changes to services
deploy_service Build + push + deploy a single service
deploy_kong Rebuild and deploy Kong gateway
deploy_lb Deploy/update load balancer
run_db_migrate Apply pending database migrations
deploy_schedulers Deploy all scheduled jobs
deploy_scheduler Deploy a single scheduled job
remove_service_cloud Remove a service from cloud
remove_detached_worker Remove a worker from cloud
infra_destroy Destroy all cloud infrastructure

Action tools — setup & CI

Tool Description
cloud_init Initialize cloud provider credentials
infra_bootstrap Bootstrap cloud project
infra_init Initialize Terraform state
infra_generate Generate Terraform files
infra_generate_docker Generate Dockerfiles
infra_build_docker Build Docker images
infra_push_docker Push Docker images to registry
infra_generate_kong Generate Kong declarative config
infra_build_kong Build Kong Docker image
infra_init_ci Initialize CI/CD workflows
infra_generate_ci Regenerate CI workflows
validate_service Validate service structure
remove_scheduler Remove a scheduled job from cloud

Resources

Resource Description
Project state (8) Services list, environments, config, infrastructure settings, deployed services, secrets, schedulers, migration status
Secrets context Local and cloud secret names with diff
Kong routes Current gateway routing configuration
Guides (4) Framework guide, workflow guide, nest-common guide, config guide

Architecture

The MCP server is a thin layer over the tsdevstack CLI:

  • Query tools either read local config files directly or wrap npx tsdevstack commands
  • Action tools delegate to runCommand() which spawns npx tsdevstack <command> as a child process
  • Resources read project files and provide contextual documentation

Community

Join the Discord: discord.gg/2EMFkqc8QR

License

Apache-2.0

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选