ForeverVM MCP Server

ForeverVM MCP Server avatar

by paulgb

Official Integrations

What is ForeverVM MCP Server

foreverVM

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cli npm
sdk npm

foreverVM provides an API for running arbitrary, stateful Python code securely.

The core concepts in foreverVM are machines and instructions.

Machines represent a stateful Python process. You interact with a machine by running instructions (Python statements and expressions) on it, and receiving the results. A machine processes one instruction at a time.

Getting started

You will need an API token (if you need one, reach out to [email protected]).

The easiest way to try out foreverVM is using the CLI. First, you will need to log in:

npx forevervm login

Once logged in, you can open a REPL interface with a new machine:

npx forevervm repl

When foreverVM starts your machine, it gives it an ID that you can later use to reconnect to it. You can reconnect to a machine like this:

npx forevervm repl [machine_name]

You can list your machines (in reverse order of creation) like this:

npx forevervm machine list

You don't need to terminate machines -- foreverVM will automatically swap them from memory to disk when they are idle, and then automatically swap them back when needed. This is what allows foreverVM to run repls β€œforever”.

Using the API

import { ForeverVM } from '@forevervm/sdk'

const token = process.env.FOREVERVM_TOKEN
if (!token) {
  throw new Error('FOREVERVM_TOKEN is not set')
}

// Initialize foreverVM
const fvm = new ForeverVM({ token })

// Connect to a new machine.
const repl = fvm.repl()

// Execute some code
let execResult = repl.exec('4 + 4')

// Get the result
console.log('result:', await execResult.result)

// We can also print stdout and stderr
execResult = repl.exec('for i in range(10):\n  print(i)')

for await (const output of execResult.output) {
  console.log(output.stream, output.data)
}

process.exit(0)

Working with Tags

You can create machines with tags and filter machines by tags:

import { ForeverVM } from '@forevervm/sdk'

const fvm = new ForeverVM({ token: process.env.FOREVERVM_TOKEN })

// Create a machine with tags
const machineResponse = await fvm.createMachine({
  tags: { 
    env: 'production', 
    owner: 'user123',
    project: 'demo'
  }
})

// List machines filtered by tags
const productionMachines = await fvm.listMachines({
  tags: { env: 'production' }
})

Memory Limits

You can create machines with memory limits by specifying the memory size in megabytes:

// Create a machine with 512MB memory limit
const machineResponse = await fvm.createMachine({
  memory_mb: 512,
})

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Frequently Asked Questions

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.

What are MCP Servers?

MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.

How do MCP Servers work?

MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.

Are MCP Servers secure?

Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.