Firefly MCP

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Discover, manage and codify cloud resources with Firefly.

What can you do with Firefly MCP?

  • 🔍 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

Install

The installation steps are in the documentation below. Documentation

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. Firefly MCP Server
  2. Features
  3. Prerequisites
  4. Installation
  5. Usage
  6. Demo
  7. Contributing
  8. License
  9. Support

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 (v20 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
  1. 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.

Frequently asked questions

What is Firefly MCP?

Discover, manage and codify cloud resources with Firefly.

How do I install Firefly MCP?

Follow the installation steps in its documentation, shown on this page and in its repository.

Is Firefly MCP open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains Firefly MCP?

It is published by gofireflyio. AI.tn lists it but does not maintain or endorse it.

From the community awesome-mcp-servers lists and the project's GitHub repository. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.