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Firefly MCP

by gofireflyio

Connects MCP clients to Firefly for discovering, managing, and codifying cloud and SaaS resources.

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Install Firefly MCP

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "gofireflyio-firefly-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@fireflyai/firefly-mcp"
      ],
      "env": {
        "FIREFLY_ACCESS_KEY": "YOUR_VALUE_HERE",
        "FIREFLY_SECRET_KEY": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Install not yet sandbox-tested— we haven't run this command through our automated sandbox yet. Not a red flag; we're working through the catalog.

Overview

The gofireflyio/firefly-mcp MCP server connects AI clients to the Firefly platform and its connected cloud and SaaS accounts. It supports resource discovery, resource management, and conversion of discovered resources into Infrastructure as Code. Authentication uses Firefly access and secret keys, supplied as environment variables or command-line arguments. Reach for it when you want Claude or Cursor to query Firefly-managed resources or generate infrastructure definitions from them.

Use cases

  • Discover resources across connected cloud accounts
  • Query SaaS resources managed through Firefly
  • Manage Firefly-connected resources with an AI client
  • Codify discovered resources into Infrastructure as Code
  • Generate Terraform from an existing cloud resource

Key features

  • Cloud and SaaS resource discovery
  • Resource management through Firefly
  • Infrastructure-as-Code codification
  • Access-key authentication
  • NPX and SSE launch options

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 3d ago

Recent health check succeeded.

19/19 checks healthy over the last 80d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 11d ago via OSV.dev · @fireflyai/firefly-mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars16Stargazers on the source repository.
npm downloads73Package downloads in the last 30 days.
Last commit16d agoMost recent push to the default branch.
Directory activity2 viewsConfig copies, upvotes, and views on AllMCPs.

How Firefly MCP works

What gofireflyio/firefly-mcp MCP server does

The gofireflyio/firefly-mcp MCP server exposes Firefly capabilities to MCP-compatible AI clients. It works with cloud and SaaS accounts connected to Firefly, allowing an agent to find resources, manage them, and turn discovered resources into Infrastructure as Code.

A typical request might identify an EC2 instance in a specific AWS account and ask the agent to codify it. The server is therefore suited to inventory queries, resource-focused investigation, and creating infrastructure definitions from existing resources.

How it works

The server is implemented in TypeScript and communicates with the Firefly platform using a Firefly account's access credentials. Clients send natural-language requests through MCP; the server uses those requests to query or act on resources available through the connected Firefly accounts.

The gofireflyio/firefly-mcp MCP server can be launched through NPX. The documented client configuration uses a local command for stdio connections. The README also demonstrates starting the process with an SSE option on port 6001 and connecting through a local /sse URL.

Setup and configuration

Node.js 20 or newer and npm or Yarn are prerequisites. A Firefly account with generated access keys is also required. Install is not necessary for the documented NPX workflow:

Terminal
npx @fireflyai/firefly-mcp

Provide credentials with FIREFLY_ACCESS_KEY and FIREFLY_SECRET_KEY, or pass them as --access-key and --secret-key arguments. For a stdio client configuration, add the NPX command and its environment variables to mcp.json. For the SSE example, start the server with --sse --port 6001, then configure the client with http://localhost:6001/sse.

The gofireflyio/firefly-mcp MCP server is documented for use with Claude and Cursor. Cursor users start the process, connect to it through Cursor's MCP settings, and can then query resources using natural language.

Tools and capabilities

Documented capabilities include:

  • Discovering resources in connected cloud accounts
  • Discovering resources in connected SaaS accounts
  • Managing resources exposed through Firefly
  • Converting discovered resources into Infrastructure as Code
  • Authenticating requests with Firefly access and secret keys

Limitations and notes

The server depends on a Firefly account and valid generated credentials. It requires Node.js 20 or later for the documented setup. Its resource coverage depends on the cloud and SaaS accounts connected to Firefly. Support and configuration details are available through Firefly's documentation or the repository issue tracker.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about Firefly MCP

gofireflyio/firefly-mcp is an MCP server that connects AI clients to the Firefly platform and lets them discover, manage, and codify resources from connected cloud and SaaS accounts. Its main capabilities cover resource discovery, resource management, and conversion into Infrastructure as Code, authenticated with Firefly access credentials.

Run it with NPX using `npx @fireflyai/firefly-mcp`; Node.js 20 or newer and npm or Yarn are required. Supply Firefly credentials through environment variables or command-line arguments, then add the command to the MCP client's configuration.

Set `FIREFLY_ACCESS_KEY` and `FIREFLY_SECRET_KEY`, or pass `--access-key` and `--secret-key` when starting the process.

Yes, gofireflyio/firefly-mcp works with Cursor. Start the server, connect to it through Cursor's MCP configuration, and use natural-language requests to query resources. The README also includes an example that finds an AWS EC2 instance and codifies it into Terraform.

Yes, it can codify discovered resources into Infrastructure as Code, and the README demonstrates Terraform output for an AWS EC2 instance.

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