Obot AI

Shadow AI and hidden MCP servers are spreading faster than IT teams can track. Get real visibility and control over what AI agents actually do in production. Start your free 2-week Obot Cloud trial.

I'm really excited about how security layers around MCP are starting to come together. Having been close to this one, I'm especially excited about the impact the new Aviatrix + Obot AI partnership is going to have. The premise is simple: every MCP server you run is an egress path your network controls probably aren't watching. Obot decides which servers an agent can call. Aviatrix decides where those servers can actually reach. The security story for #MCP is comigng together really cleanly - when possible run integration points behind a gateway in a network protected environemnt. When necessary, run MCPs and Skills locally, with local controls and protections. Reduce blast radius. Keep the AI momentum. #AISecurity

A few weeks ago I shared some initial thoughts on an MCP maturity model after GitHub Universe. The response was very positive, so I decided to actually build the model out. Today I've published the first version, which includes: -Detailed characteristics for all four stages - Readiness checklists (infrastructure, governance, operations) - Implementation guidance and architecture patterns - Timeline expectations and resource requirements - Real progression criteria‚ when you're actually ready to move forward Key insights from building this out: You can't skip stages. Organizations that try to jump from shadow adoption to scaled deployment get stuck. Stage 2 infrastructure looks different from Stage 3 for good reasons. Stage 1 is already happening. MCPs are all over your company and the only question is if you're aware of them. The Stage 2 - Stage 3 transition is the big lift. Going from managed pilot to scaled deployment is where most organizations will spend time. It's the shift from "IT provides MCPs" to "anyone can build assistants." This framework reflects patterns we're seeing at Obot AI from users and enterprise teams. It's the same progression we've seen with cloud, containers, and SaaS‚ just applied to MCP adoption. Link to full document model in comments. #MCP #EnterpriseAI #ModelContextProtocol #EnterpriseAI #AIAdoption #AIGovernance #PlatformEngineering #EnterpriseArchitecture #AIInfrastructure #OpenSource #Obot

Your org is already experimenting with MCP. But without governance, it turns into shadow infrastructure fast. Obot MCP Gateway gives IT a single control plane to onboard, secure, and audit MCP servers across the enterprise. Identity-aware access, curated catalogs, full audit logs — all open source.

Every new AI initiative wants to integrate with internal systems via MCP. But building one-off connectors for every team doesn’t scale. Obot MCP Gateway gives developers a safe, searchable catalog of approved MCP servers. IT sets the policies once. Teams self-serve securely.

The organizations you compete with are already building governed MCP platforms. Don’t be the last one to standardize it. We’ll show you how to get started in weeks, not months.