🚀 Introducing Natoma’s Hosted MCP Platform — the fastest, easiest way to connect agentic AI to your enterprise tools & data. Forget messy API integrations. Think: 3 steps to deploy AI agents at scale. Let us explain 🧵👇

LLM Firewalls are essential for content safety. But they can't govern what AI agents actually do. Tool calls, parameter validation, and access controls fall outside their scope. An MCP Gateway completes your AI security stack by governing actions, not just language.

Your company has a decade of knowledge buried across Confluence, Slack, and SharePoint. Vector databases make it all searchable by concept, not just keyword. Your AI finds "expense submission policy" when someone searches "how do I get reimbursed." A breakdown of how they work

The difference between experimental AI and production-ready AI? Four layers of governance. Natoma provides: identity-aware permissions, tool validation, data safety, and audit trails. It's how enterprises scale AI confidently. https://t.co/9V9kcNWWcj #EnterpriseAI

AI guardrails aren't about slowing innovation. They're what make it possible at scale. We mapped the 4 levels every enterprise needs, from prompt filtering to action governance ↓ https://t.co/L06qkB3bGS #EnterpriseAI #MCP #AgenticAI

Google just launched Workspace Studio for AI agents. Microsoft has Copilot. Every platform is racing toward agentic AI. The question isn't whether agents will transform work. It's whether your infrastructure can scale when managing thousands of them. More about Google Workspace

Here's what we're seeing across enterprises: 2-5 people can now supervise 50-100 AI agents executing complete workflows. Traditional hierarchies take 6 months to deploy each tool. Cross-functional agentic teams with protocol-based infrastructure like MCP Gateway do it in

AI agents represent a fundamental shift: from passive assistant to active operator. When AI can query databases, update CRMs, and orchestrate workflows, you need more than MCP. You need governance that makes agents enterprise-ready. The winners built infrastructure first.

Wishing everyone a Happy Thanksgiving from our family to yours! We're grateful for our customers, partners, and the amazing community of builders shaping the future of AI with us. #HappyThanksgiving

OpenAI built ChatGPT Apps on MCP—800M+ users now rely on this protocol. The question for enterprises isn't if, it's how. What is an MCP Gateway? ↓

Vibe building AI experiences >>> debugging OAuth at 11pm Your engineers deserve better https://t.co/XbsrS3ftrM

Enterprise AI deployment just got radically simpler. Natoma's Managed MCP Gateway: 100+ verified servers, one-click deploy, complete audit trails built-in. Turns months of integration work into minutes. How fast could your teams move without infrastructure bottlenecks?

Power healthcare with AI. Zero friction. Natoma's MCP Gateway delivers plug-and-play EPIC and Cerner integrations. HIPAA-compliant connections, patient data protection, audit-ready logging. Deploy in minutes, not months. https://t.co/0Oz0HTn21N

Today we honor the courage, dedication, and sacrifice of all who have served. To every veteran: thank you for protecting the freedoms that enable us to innovate, build, and serve our communities. Your service inspires us every day. 🤝 #VeteransDay

47 seconds from download to deployment. No custom code. No security reviews. No months of integration work. Watch: GitHub + Asana+ Claude connected in under a minute. → Copy snippet → Authenticate → Ship This is zero friction. This is Natoma.

Financial services moves at market speed. Your AI infrastructure should too. Traditional integrations: 3-6 months Natoma's MCP Gateway: Minutes You can now deploy AI across trading, risk, and operations instantly. Experience Natoma: https://t.co/XbsrS3ftrM #FinTech

Week 12 of building AI infrastructure vs. Day 1 with a managed MCP Gateway. Your developers shouldn't spend months on integration plumbing. 100+ verified servers. One-click deployment. 47 seconds to production. Which timeline are you on? #EnterpriseAI #MCPGateway

"What's the ROI on AI adoption?" Most orgs measure activity (pilots) vs outcomes (productivity). The key: establish baselines first. Otherwise you're measuring anecdotes. Framework:

Ever tried building an MCP Server? MCP is the "USB-C port" for AI: one protocol, works everywhere. → Auto-generate with FastMCP → Test with Inspector → Deploy to any client Build for tomorrow's AI, not just today's. 👉 Use our MCP Developers Guide to build your first MCP

You've proven AI works. Your team loves it. Productivity is up. Then you try to scale and hit a wall. 3-6 months per tool. Custom integration hell. There's a better way. Protocol-based architecture. Minutes instead of months. Learn how with @natomalabs

Your enterprise has 225 MCP servers running. You just don't know it. MCP Gateways create the control point where every AI interaction is authenticated, authorized, and audited. Deploy in minutes, not months. 100+ integrations ready. https://t.co/SLr5ElEUNi #EnterpriseAI