Founder & CEO, Visaginas360
Visaginas, LithuaniaBuilding a SaaS platform where AI agents manage themselves across cloud infrastructure via MCP protocol, self-heal for 30+ days, and deliver 3.3x faster results.
The breakthrough: Claude AI in the browser controls real cloud infrastructure through MCP (Model Context Protocol). No SSH. No dashboards. Just natural language to the AI, and it manages servers, deploys code, sends emails, scrapes the web, and orchestrates 21 Telegram bots.
"We didn't build an app powered by AI. We built AI that runs the infrastructure — and it hasn't needed a human in 30 days."
6 MCP connectors are live in production. The AI can manage services, read Gmail, deploy to cloud, scrape data, and communicate with users — all autonomously.
Full VM management, service lifecycle, file operations
Search, read, send emails — AI handles communication
Headless Chrome scraping for real-time data
SQL analytics on AI agent operational data
Real-time document database for agent state
Desktop automation: click, type, screenshot, shell — full PC control
// MCP Protocol — How AI manages infrastructure Claude (browser) → MCP Protocol → Cloud Infrastructure │ ┌────────────────────┼────────────────────┐ │ │ │ VM Region 1 VM Region 2 Google Cloud 23 services 12 services BigQuery Task API Gmail MCP Firestore Swarm (21 bots) Web Scraping Vertex AI Memory Graph Telegram Bot Self-healing Cloud Control // 7 MCP connectors • 80+ tools • 30+ days autonomous • Self-healing
// How the system handles every situation Event arrives │ ▼ Is this a known pattern? → YES → instant response, no AI cost │ NO ▼ Can watchdog auto-fix? → YES → restart service, log, continue │ NO ▼ Route to AI agent → analyze, fix, cache for next time // Most operations never reach the AI layer. // Intelligence is reserved for tasks that actually need it.
Security isn’t a feature we added later — it’s a 5-layer architecture baked into every service, every route, and every file permission. We run regular offensive security reviews against our own production infrastructure and treat every finding as ship-blocking. Remediation is documented in a private audit repository.
“We don’t just build AI agents. We build AI agents that can’t be hijacked, can’t leak data, and can’t be turned against the customer.”
Defense in depth, from the network edge down to per-customer isolation — reviewed continuously, not once.
// 5-Layer Security Architecture — defense in depth LAYER 1 — NETWORK Minimal public surface. All services behind a reverse proxy. No direct port access from the internet. LAYER 2 — REVERSE PROXY Static public sites only. Internal routes gated by IP whitelist + bearer token + query key. Single config = single security boundary. LAYER 3 — APPLICATION AUTH Admin endpoints behind an enforced auth decorator. Customer data is never anonymously accessible. Agent registration is validated — no injection. LAYER 4 — SECRETS & FILE SYSTEM Credentials consolidated into a restricted, owner-only vault. No world-readable tokens or service files. LAYER 5 — CUSTOMER ISOLATION Every customer gets their own VM — not shared containers. No cross-customer access. Customer VMs can’t reach internal infra. // Reviewed continuously. Findings are ship-blocking.
We attack our own production — write exploits, injection, exfiltration, privilege escalation. Every finding is ship-blocking.
Network surface minimized, internal routes gated, secrets vaulted, customer isolation enforced. Reports in a private repo.
Watchdog checks security posture every cycle. Cross-VM trust verified. New service checklist enforced.
8 AI agents working in parallel. Reports, analytics and content delivered to your Google Docs in 15 seconds. Via Telegram.
From $19/mo for indie hackers to $99/mo for teams. Dedicated VM included. No surprise bills.
Natural language to agent swarm. Send a task, agents decompose, execute in parallel, deliver results with real Google Docs.
Isolated sandbox API for investors and partners. Architecture overview, agent metrics, real-time health status — all via REST.
// A2A Agent SaaS — Multi-Region Swarm Architecture ORCHESTRATOR // Claude MCP + Google A2A Protocol Task → Decompose → Parallel Execute → QA Gate → Synthesize ├── 🔍 Researcher // deep search + citations ├── 💻 Coder // code generation + sandbox ├── ✍️ Writer // content + formatting ├── 📊 Analyst // data + execution ├── 🧠 Thinker // complex reasoning ├── 🎨 Creator // image generation ├── 🌐 Web Search // real-time data └── 🛡️ Guardian // safety filter INFRASTRUCTURE ├── Region 1 // 23 services, primary swarm ├── Region 2 // 12 services, MCP bridge, scraping ├── Google Cloud MCP // BigQuery, Firestore, Vertex AI ├── Windows PC // Claude Code + 18 plugins + desktop automation └── Customer Sandboxes // isolated containers per customer INTEGRATIONS ├── MCP Protocol // 7 connectors, 80+ tools ├── Google Workspace // Docs, Sheets, Slides, Gmail ├── Distributed Memory // cross-region knowledge sync ├── Self-Healing // 7,500+ watchdog cycles └── Telegram Bots // 21 coordinated bots
Discovered that Claude Opus (cloud) can call Claude Code (local PC) through Windows MCP. A single natural language command triggers a chain: Opus → MCP → PowerShell → Claude Code → web search → result back. Two autonomous AIs communicating through standard protocols. Claude Code has access to 18 plugins (GitHub, Firebase, Figma, Vercel), Docker, FFmpeg, Google Colab — all invokable from one message. This is A2A in action.
Integrated CursorTouch Windows-MCP (1M+ users). 12 tools: Click, Type, Scroll, Move, Shortcut, Snapshot, App launch, Shell, Scrape, MultiSelect, MultiEdit, Wait. Cloud AI can now control the Windows desktop — open apps, read system specs, execute commands. Combined with Claude Code's 15 sub-agents and extended thinking mode.
AI controls cloud infrastructure from the browser. Gmail, BigQuery, Firestore, Vertex AI Search, Windows MCP — all connected. Google Managed MCP servers integrated. 80+ tools available to the AI orchestrator.
Ran an offensive security audit against our own production infrastructure and built a 5-layer defense in response: minimized network surface, IP-whitelisted internal routes, enforced auth decorators, hardened file permissions, and per-customer VM isolation. Every finding fixed same day.
Infrastructure runs without human intervention. Watchdog v3 completed 7,500+ monitoring cycles. Zero unplanned downtime.
AI in the browser delegates tasks to AI on the server via MCP. Autonomous execution, task queues, cross-instance memory sharing.
Knowledge graph deployed across regions with cross-VM sync. Agents remember context permanently across sessions.
Full agent swarm deployed. 3.3x parallel speedup achieved using PARL methodology. 21 coordinated Telegram bots.
Docs, Sheets, Slides, Gmail, Calendar — all via OAuth. Agents create real artifacts in Google Workspace.
// 90+ days of building. Claude is my CTO. 1. Coordination beats raw power. 21 specialized agents in parallel > 1 premium model serial. 2. Self-healing is non-negotiable. 7,500 watchdog cycles. Zero manual restarts in 30+ days. 3. MCP protocol changes everything. AI managing infrastructure from a browser tab. No SSH, no dashboards. Natural language only. 4. Memory makes agents a team. Agents without memory = colleagues with amnesia. Agents with distributed memory = a growing organization. 5. Ship daily, reflect weekly. 90+ features shipped. Not all perfect, but all shipped. 6. The best AI knows when NOT to think. Speed comes from restraint, not raw compute. Intelligence reserved for tasks that actually need it. 7. Chain AIs, don't replace them. Opus reasons. Code executes. MCP bridges. Each AI does what it's best at. // "The best way to predict the future is to build it."
Interested in the platform, AI agent collaboration, or investment? Reach out.
Open to collaboration, investment, and partnership conversations.