Which integrations are available for this server?

Required runtime environment for the MCP server Enables converting discovered cloud resources into Terraform infrastructure as code The programming language used to build the MCP server Supports discovery and management of Ubuntu instances in cloud environments

How do I use Firefly?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Firefly find all EC2 instances in my AWS account and show their Terraform code" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Firefly

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

Related MCP server: Apifox MCP

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:

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_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

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

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

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

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.

This server cannot be installed

-

security - not tested

A

license - permissive license

-

quality - not tested

How are these scores calculated?

Resources

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