Bring your own AI · For IT and platform teams
Enterprise MCP
Bring your own AI. We’ll bring the apps.
One MCP layer that gives Claude, ChatGPT, Cursor, LangChain — any agent — governed access to 250+ enterprise applications and any internal API. Built once, reused by every AI client, every workflow, and every Teammate.
Open by design
One tool layer. Every AI surface.
Every enterprise system.
The AI you bring, the assistant you use, and the Teammates you hire all call the same tools — through one integration.
How it works
Build once. Use everywhere. Govern centrally.
One integration per system, exposed as a governed MCP tool. Every AI client, every workflow, and every Teammate reuses it — under the same permissions and the same audit trail.
Build once, use in every AI client
Create a tool integration once. FlowGenX exposes it to every AI client and agent framework — no per-app, per-framework rewiring.
Any API becomes a tool
250+ managed connectors out of the box. Import an OpenAPI spec or Postman collection and it becomes a governed MCP tool.
Govern centrally
Who can use which tool, with which permissions, at which approval tier — and one audit trail across every AI surface.
Beyond APIs
Built-in browser automation drives real browsers through the systems that have no API — forms, portals, legacy UIs.
Faster time-to-production vs custom integrations
Reduction in integration cost per AI surface
Integration serves every AI app & framework
Pre-built enterprise connectors
The problem at scale
AI adoption is stalling — and integration debt is why
Duplicate integrations
per AI app or agent framework. Each requires its own connector code, auth logic, and maintenance.
Average security review
before any AI tool goes live. Fragmented governance means every tool gets reviewed from scratch.
Of AI pilots stall
before reaching production. The #1 blocker: AI tools can't access the systems where work happens.
The compounding problem
Every workaround makes the next one harder
Every new AI app needs its own connectors
= weeks of dev time per tool, per system
Every agent framework has a different tool spec
= tools built for one framework can't be reused in another
No unified governance across AI experiences
= security reviews bottleneck every deployment
Shadow AI tools bypass enterprise controls
= data leakage risk with every ungoverned copilot
Opportunity Cost Per Year
“We were spending more time integrating tools than building AI features.”
— VP Engineering, Fortune 500
Three ways in, one engine
IT says yes once — not three times
The tools, permissions, and audit trail you set up for Enterprise MCP are the same ones behind FlowGenX Chat and every Teammate. A personal gateway can’t do that.
Connect every AI your company uses
to every app it runs — in one layer
See how Enterprise MCP replaces per-app, per-framework integrations with one governed tool layer — and how the same tools power FlowGenX Chat and Teammates.