Nutanix Agent Gateway
by Nutanix
A unified control plane to govern AI agent traffic, cost, and access across the enterprise
Nutanix Agent Gateway is a centralized control plane that governs how AI agents access LLMs and Model Context Protocol (MCP) tools, with token observability, access policies, audit logging, and a unified API for external and self-hosted models. It targets IT and platform teams trying to tame agent sprawl and AI cost.
Introduced as part of Nutanix Enterprise AI 2.7 in 2026, Nutanix Agent Gateway is an AI control plane that sits between users, applications, and AI models to centralize governance and cost control for autonomous agents. It manages traffic between agents, large language models, and MCP servers connecting to business tools, offering token observability (visibility into token usage, MCP access, and LLM activity across multiple model vendors), granular access-control policies for MCP servers, comprehensive audit logs of every request for compliance, a single unified API for both external provider models and self-hosted models, and token-based rate limiting to enforce quotas across agents and teams. Nutanix positions it against 'agent sprawl' and runaway inference spend — CEO Rajiv Ramaswami framed the pre-gateway status quo as 'a free-for-all' — pitching cost attribution and model routing that appeal to CFOs and COOs as well as CIOs. It deploys rapidly on public cloud or supported Kubernetes infrastructure, with MCP-server governance features shipping in Tech Preview.
At a Glance
- Category
- Governance & Security
- Pricing
- Contact for pricing
- Target Market
- CIOs, CTOs, CFOs, Platform Engineers
Key Features
- ✓Token observability
Centralizes visibility into token usage, MCP server access, and LLM activity across multiple model vendors.
- ✓MCP access control
Granular policies let agents securely connect to business tools and data via Model Context Protocol servers.
- ✓Audit logs
Comprehensive records of every MCP and model request for compliance and traceability.
- ✓Unified model API
A single interface for accessing both external provider models and self-hosted models.
- ✓Token-based rate limiting
Real-time enforcement of quotas and cost controls across agents and teams.
- ✓Model routing
Routes requests to appropriately sized models based on use-case complexity to control spend.
Capabilities
Use Cases
- •Rein in agent sprawl
Give platform teams one control point over which agents can use which models and tools.
- •AI cost governance
Attribute token spend by user, workload, and team and enforce quotas to prevent runaway costs.
- •Compliant model access
Log and audit every model and MCP request for security and compliance.
Ideal For
Best For
- ✓Centralized governance of AI agent and LLM traffic
- ✓Attributing and controlling AI token cost
- ✓Securing agent access to MCP tools and data
Deployment
Market Analysis
Pros
- ✓Single control point for agent, LLM, and MCP traffic
- ✓Strong cost-attribution and token-governance story
- ✓Deploys on existing cloud or Kubernetes infrastructure
Cons
- ✗MCP-server governance features still in Tech Preview
- ✗Pricing not publicly disclosed
Pricing
Nutanix Enterprise AI
Contact for pricing
- ✓Delivered with Nutanix Enterprise AI 2.7
- ✓Token observability and rate limiting
- ✓MCP governance and audit logs
- ✓Unified model API
Delivered as part of Nutanix Enterprise AI 2.7; pricing is not publicly disclosed.
Sources
This page was written from 2 sources, 1 on domains other than nutanix.com.
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