连接能力
gofireflyio firefly mcp 为 AI Agent 提供什么
- 🔍 Resource Discovery: Find any resource in your Cloud and SaaS accounts
- 📝 Resource Codification: Convert discovered resources into Infrastructure as Code
- 🔐 Secure Authentication: Uses FIREFLY_ACCESS_KEY and FIREFLY_SECRET_KEY for secure communication
- 🚀 Easy Integration: Works seamlessly with Claude and Cursor
- Node.js (v14 or higher)
- npm or yarn
- Firefly account with generated access keys
- Using environment variables:
- Using arguments:
- Start the MCP server using one of the methods above
- Use the Cursor extension to connect to the MCP server - see [Cursor Model Context Protocol documentation](https://docs.cursor.com/context/model-context-protocol)
- Use natural language to query your resources
- Fork the repository
- Create your feature branch (`git checkout -b feature/amazing-feature`)
- Commit your changes (`git commit -m 'feat: Add amazing feature'`)
- Push to the branch (`git push origin feature/amazing-feature`)
- Open a Pull Request
安全
MCP 收录不等于安全审核
MCP 服务器可能获得模型上下文、凭据、本地文件或调用外部系统的权限。连接 Agent 前,请检查代码、环境变量、网络行为、软件包来源与维护状态。
README
仓库文档
The Firefly MCP (Model Context Protocol) server is a TypeScript-based server that enables seamless integration with the Firefly platform. It allows you to discover, manage, and codify resources across your Cloud and SaaS accounts connected to Firefly.
- 🔍 Resource Discovery: Find any resource in your Cloud and SaaS accounts
- 📝 Resource Codification: Convert discovered resources into Infrastructure as Code
- 🔐 Secure Authentication: Uses FIREFLY_ACCESS_KEY and FIREFLY_SECRET_KEY for secure communication
- 🚀 Easy Integration: Works seamlessly with Claude and Cursor
- Node.js (v20 or higher)
- npm or yarn
- Firefly account with generated access keys
You can run the Firefly MCP server directly using NPX:
npx @fireflyai/firefly-mcpYou can provide your Firefly credentials in two ways:
- Using environment variables:
FIREFLY_ACCESS_KEY=your_access_key FIREFLY_SECRET_KEY=your_secret_key npx @fireflyai/firefly-mcp- Using arguments:
npx @fireflyai/firefly-mcp --access-key your_access_key --secret-key your_secret_keyUpdate the mcp.json file with the following:
{
"mcpServers": {
"firefly": {
"command": "npx",
"args": ["-y", "@fireflyai/firefly-mcp"],
"env": {
"FIREFLY_ACCESS_KEY": "your_access_key",
"FIREFLY_SECRET_KEY": "your_secret_key"
}
}
}
}Run the MCP server using one of the methods above with the following command:
npx @fireflyai/firefly-mcp --sse --port 6001Update the mcp.json file with the following:
{
"mcpServers": {
"firefly": {
"url": "http://localhost:6001/sse"
}
}
}- Start the MCP server using one of the methods above
- Use the Cursor extension to connect to the MCP server - see Cursor Model Context Protocol documentation
- Use natural language to query your resources
Find all "ubuntu-prod" EC2 instance in 123456789012 AWS account and codify it into Terraform
resource "aws_instance" "ubuntu-prod" {
ami = "ami-0c55b159cbfafe1f0"
instance_type = "t3.micro"
}
Demo.mov
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'feat: Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
For support, please visit Firefly's documentation or create an issue in this repository.
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