What is Firefly Mcp

Firefly MCP is a TypeScript-based server that facilitates integration with the Firefly platform, allowing users to discover, manage, and codify resources across their Cloud and SaaS accounts.

Use cases

Use cases for Firefly MCP include automating resource management, enhancing security through codification, and integrating with other platforms for streamlined operations.

How to use

To use Firefly MCP, install it via NPX and provide your Firefly credentials either through environment variables or command-line arguments. Start the server and configure it in the ‘mcp.json’ file to connect with other services.

Key features

Key features include resource discovery across Cloud and SaaS accounts, resource codification into Infrastructure as Code, secure authentication using access keys, and easy integration with tools like Claude and Cursor.

Where to use

Firefly MCP can be used in cloud management, DevOps practices, and SaaS resource management, making it suitable for organizations leveraging multiple cloud services.

Firefly MCP Server

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.

Features

• 🔍 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

Prerequisites

• Node.js (v14 or higher)
• npm or yarn
• Firefly account with generated access keys

Installation

You can run the Firefly MCP server directly using NPX:

npx @fireflyai/firefly-mcp

Environment Variables

You can provide your Firefly credentials in two ways:

1. Using environment variables:

FIREFLY_ACCESS_KEY=your_access_key FIREFLY_SECRET_KEY=your_secret_key npx @fireflyai/firefly-mcp

2. Using arguments:

npx @fireflyai/firefly-mcp --access-key your_access_key --secret-key your_secret_key

Usage

Stdio

Update 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 6001

Update the mcp.json file with the following:

{
  "mcpServers": {
    "firefly": {
      "url": "http://localhost:6001/sse"
    }
  }
}

Using with Cursor

1. Start the MCP server using one of the methods above
2. Use the Cursor extension to connect to the MCP server - see Cursor Model Context Protocol documentation
3. Use natural language to query your resources

Example:

Prompt

Find all "ubuntu-prod" EC2 instance in 123456789012 AWS account and codify it into Terraform

Response

resource "aws_instance" "ubuntu-prod" {
  ami           = "ami-0c55b159cbfafe1f0"
  instance_type = "t3.micro"
}

Demo

https://github.com/user-attachments/assets/0986dff5-d433-4d82-9564-876b8215b61e

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'feat: Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For support, please visit Firefly’s documentation or create an issue in this repository.