What are the prerequisites to run BRAINS OS - version MCP?
You need Node.js v16 or later, an AWS account with configured credentials, and Git.
@groovysquirrel
基本信息
A Serverless MCP implementation using SST, React and AWS.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"brains-mcp": {
"command": "npx",
"args": [
"sst",
"dev"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
A modern, serverless operating system for AI systems and agents, built with SST, React, and TypeScript. It provides a robust framework for managing Large Language Models (LLMs) and specialized AI agents through the MCP (Model Control Protocol) with a unified command system and shared operating template.
Clone the repository, install dependencies with npm install, and start the development server using npx sst dev. Configure test environment by copying .env.test.example to .env.test and setting AWS Cognito credentials, then run test scripts located in packages/brainsOS/test_scripts/mcp/.
You need Node.js v16 or later, an AWS account with configured credentials, and Git.
It uses AWS Lambda for backend functions, AWS Cognito for authentication, DynamoDB for database, and SST (Serverless Stack) for infrastructure management.
Fork the repository, create a feature branch, commit changes, and open a Pull Request.
Never commit `.env.test` to version control, set file permissions to 600 (`chmod 600 .env.test`), rotate credentials regularly, and use separate test credentials from production.
Test scripts are organized under `packages/brainsOS/test_scripts/` with subdirectories for MCP, resources, and services. You can run individual suites like `./packages/brainsOS/test_scripts/mcp/test_tools.sh` with options to start from a specific step.
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