The era of the always-on virtual private server is officially over.

Meet JARVIS, an ultra-autonomous, serverless AI agent framework. Engineered strictly inside GitHub Actions. No databases, no persistent VMs, no manual human-in-the-loop dependencies. Set, forget, and let automated workflows heal, build, and trigger self-maintaining pipelines.

Operational Cost

0$ Infrastructure

Pay only direct LLM tokens

Platform Trigger

GitHub Actions

Completely serverless cron

Modular Skills

121+ Cataloged

Instant Markdown prompts

Self-Healing

Continuous Auto-Patch

LLM evaluations and patches

Zero-Click Provisioning

Install with a Single Terminal Line

Deploying JARVIS is completely frictionless. We have packaged our multi-agent architecture into a direct script-based builder that connects natively to your secure repository layout.

1

Authentication Handshake: The installer asks for your secure GitHub Personal Access Token (PAT) with repository and workflow scopes.

2

Private Repository Initialization: JARVIS creates a new private, dedicated repository directly in your account to shield your workflows.

3

Automatic Agent Commit: The entire actions codebase, scheduling directory, and workflow secrets are committed securely and activated.

Need a GitHub Token? Click here to get one.

Direct Setup Bootstrap

Copy and paste this bootstrap command into your local terminal environment to trigger the self-healing installer.

>_ curl -fsSL https://jarvisai.fun/install | bash

Setup Execution Checklist

AUTOMATED DEPLOYMENT
User Token Exchange Validates and links your secure GitHub Personal Access Token (PAT).
github-pat handshake
Instantiate Private Repos Provisions a fully-encrypted private operational workspace repository.
secure repository spinup
Automated Base Commit Pushes core serverless action workflows and initializes tasks.
deployment activation
Skills Showcase

The Modular Prompt Library

Every capability runs inside containerized, secure environments with built-in allow/block rules.

Academic Briefing Core

Deep Literature Synthesis

Parses Semantic Scholar searches and ArXiv files based on targeted keyword alerts, compiling synthesized markdown reports asynchronously.

CLI Command./run-skill --id research
DependenciesTavily, Semantic Scholar
Avg. Cost~$0.04 per compile
Ledger Monitoring Crypto Pack

On-Chain Activity Tracker

Queries Alchemy endpoints to track massive token movements, smart contract deployments, and liquidity trends in real-time.

CLI Command./run-skill --id ledger-watch
DependenciesAlchemy API, Etherscan
Avg. Cost~$0.01 per run
Self-Healing Core

Autonomous PR Reviews

Listens to repository issue label `ai-build`. Automatically pulls code differences, evaluates architecture, resolves conflicts, and designs PRs.

CLI Command./run-skill --id auton-pr
DependenciesGitHub Actions SDK
Avg. Cost~$0.08 per branch
Privacy Inference Community

Venice AI Privacy Engine

Incorporate private local inference routing into active execution blocks. Bypasses persistent cloud storage metrics completely.

CLI Command./install-skill-pack venice
DependenciesVenice API Handshake
Avg. CostFree Tier Eligible
Protocol Gateway Core

MCP Desktop Tool Exposer

Exposes the localized catalog of prompts as native Model Context Protocol (MCP) tools inside Claude Desktop or Claude Code interfaces.

CLI Command./run-skill --id mcp-server
DependenciesModel Context Protocol
Avg. Cost~$0.02 per query
Market Synthesis Community

DeFi Intel Synthesis

Auto-gathers decentralized pool data, volume metrics, and on-chain protocol upgrades, publishing a beautifully compiled brief daily.

CLI Command./install-skill-pack finance
DependenciesCoingecko API, DefiLlama
Avg. Cost~$0.03 per digest

Complex Skill Chaining (Pipeline Composition)

JARVIS supports parallel and sequential skill chaining configured directly via jarvis.yml. Configure one skill to execute and pass its output files directly as downstream context (State Passing), or run research and data collection in parallel before a synthesis skill consumes both outputs (Complex Workflows).

Sequential State Passing Parallel Orchestration

The Manifesto

Designed to eliminate human babysitting.

Most modern AI frameworks require expensive, persistent cloud servers and hours of manual supervision. If an API updates, they break. If a memory limit is reached, they crash.

JARVIS is engineered strictly under a zero-trust, absolute-autonomy paradigm. By executing native pipelines via Scheduled GitHub workflows, it manages state, triggers actions, integrates into chats, monitors security parameters, and heals its own system files asynchronously.

Sandbox Fallback Patterns (Bypassing GitHub Limits): To navigate strict runner constraints and prevent sandbox network blocks, JARVIS utilizes intelligent pre-fetching (caching authenticated APIs before Claude boots up) and post-processing (queuing background tasks like Discord notifications or Replicate API executions to dispatch immediately after the core LLM step finishes execution).

Zero-Server Orchestration

Runs inside containerized GitHub runners. Triggers on cron, repository events, webhooks, or platform integrations. No constant server fees, Docker compose bugs, or hosting setups.

Deep Chat Platform Links

Connect Telegram, Discord, and Slack via repository secrets. Live outbound & inbound polling allows you to interact with, command, and guide your active agent directly from your chat app.

Modular Markdown Skills

With over 121 modular skills cataloged as simple Markdown prompts, extending capabilities takes seconds. Built-in support for secure execution and vulnerability scanning on skill downloads.

Self-Healing Infrastructure

A built-in evaluation engine grades operations. If an output slips or an API fails continuously, JARVIS initiates diagnostic routines, writes updated repository code, and commits patches to repair itself.

Engineering Layout

The Mechanics of Absolute Independence

Under the hood, JARVIS replaces centralized cloud operations with clean, highly resilient, and modern protocols.

Module 01

Platform Integrations

Premium two-way messaging with outbound reports & inbound control. Native integrations poll Slack, Telegram, and Discord using offset-based polling and reaction acknowledgments to command your active agent live directly from your chat app.

  • Telegram: Bidirectional bot token control
  • Discord: Incoming trackers & webhooks
  • Slack: Bot scopes with history access
  • Email: Structured dispatch via SendGrid
Auto-activated via repository secrets
Module 02

Gateways & Secure Protocols

Connect external systems cleanly with deep support for modern Agent-to-Agent communication protocols and security barriers.

  • Fleet Watcher: Inline allow/block authorization
  • MCP Integration: @json-render/mcp renders rich visual cards
  • A2A Gateways: LangChain & AutoGen integration
  • Safe Installs: Built-in vulnerability scanners
Secure execution of external tools
Module 03

Core Operational Skills

Power complex operational pipelines that act immediately on triggers. Build complex intelligence reports, monitor trends, or run development scripts.

  • Deep Research: RSS, literature, & systematic briefs
  • Crypto Trackers: On-chain movements & market alerts
  • Auton PR Build: Resolve issues labeled `ai-build`
  • Custom Packs: Multi-agent prompt directory integration
Over 121+ custom prompts supported
Framework Comparison Benchmarks

How JARVIS Compares

A direct look at runtime efficiency, operational overhead, and persistence models compared to other heavyweight orchestration systems.

Framework Hosting Cost Runtime Setup Persistent Memory
JARVIS $0.00 Base (Serverless) GitHub Runner (On-Demand) Git-Backed JSON/State
AutoGen $30+/mo (VMs/Docker) Continuous Python Process Local DB / Disk
CrewAI $20+/mo (Cloud VM) Dockerized Container Stack ChromaDB / Vector Local
n8n $20+/mo (Self-Host/Cloud) Node.js Express Server PostgreSQL / SQLite
LangGraph Variable (Cloud Server) Python State Engine Server LangMem / Redis
Live Execution Demo

Watch absolute autonomy in motion.

See how JARVIS responds autonomously to issues, evaluates output accuracy, and repairs its own code without manual oversight.

Click the buttons on the console to trigger agents and observe real-time simulated processes.

Serverless Runner — runner-github-action-24
Live Terminal

Ready to initiate workflow execution. Trigger an event using the control panel on the left.

jarvis-auth-host ~ waiting for dispatch input...

$
Ctrl + C to abort
VOICE ENGINE: DYNAMIC
STATUS: STANDBY

Detecting System Voices...

Loading localized neural speech synthesis directories from your browser storage...

SYNTHESIS MONITOR

"Systems ready. Select a voice below to preview synthesis."

Telemetry Protocols

Local Workspace Dashboard, Speech & MCP Interfaces

JARVIS integrates localized neural speech processing, interactive desktop UI controllers, and Model Context Protocol (MCP) bridges directly into your browser context, executing complex asynchronous task routines without persistent cloud upkeep.

Vocal Directive Architecture
Zero-Cloud Neural Core

JARVIS processes speech triggers natively on device. Audio streams are transcribed and parsed through hardware-accelerated speech synthesis and recognition engines, achieving sub-150ms execution loops without sending voice data to external servers.

Local Dashboard & MCP Integrations
Local Operating Environment

Run a premium Next.js dashboard UI locally on localhost:5555. Modify briefs, manage credentials, and toggle skills on/off with full state-changing capacity. Benefit from native support for Model Context Protocol (MCP) server integration, specifically @json-render/mcp, rendering rich, interactive visual cards for your skills in real time.

Connect the elevenlabs.io API for hyper-realistic, dynamic custom neural system voices.
Deployment Center

Interactive jarvis.yml Builder

Generate and download your custom autonomous configuration instantly. Just place it into your repository secrets and run.

1. Choose Communication Hubs

Select the channels where your JARVIS should talk, accept command inputs, or push alerts.

2. Enable Core System Skills

Equip your autonomous framework with the correct capabilities on build.

3. Setup Gateway Settings

Config Preview — jarvis.yml
Save to .github/workflows/jarvis.yml YAML Schema Active
Action successful