Power your AI with enterprise data.
Supercharge your AI applications with a secure, scalable MCP platform.
Accelerate enterprise adoption of Agentic AI
Drive AI innovation across your organization while maintaining centralized oversight, granular control, & robust security
Full visibility & control
Track every tool call with audit logs and anomaly detection, fully integrated with your SIEM
Secure data handling
Block sensitive data, rate-limit calls, set budget and cap usage by user, team, or app. Prevent over-consumption. Automatic retries and backoffs when needed
Flexible deployment
Easily deploy and manage MCP servers across cloud, on-premises infrastructure, local desktops, or connect via proxy to third-party MCPs
Access controls & policies
Maintain control over what end users can see and do based on their roles and responsibilities. Centrally enable or disable tools from one place
“It has enabled our AI platform to make it effortless for all business users to query and prompt across fragmented systems in our hybrid environments - without compromising access controls, data controls, or privilege management.”
Enterprise Architect
Trusted by enterprises like
Accelerate growth, foster innovation, and enable collaboration across your entire enterprise
Frictionless experience
Improve developer productivity by giving context to coding agents.
Accelerate innovation
Streamline the adoption and integration of AI into your enterprise systems with 1-click connections.
Improve efficiency
Boost IT efficiency with AI-driven automations seamlessly integrated into your IT tools
Boost productivity
Easily connect AI agents to any data source to unlock productivity from go-to-market to finance.
MCP Gateway Architecture
How Our Model Context Protocol Platform Works
Natoma's MCP Hub serves as the orchestration layer between AI agents and enterprise systems:
1
AI Agent Request
LLMs and AI platforms send requests via standard MCP protocol
2
Gateway Processing
Our MCP Gateway authenticates, authorizes, and routes requests
3
MCP Server Execution
Target Model Context Protocol server processes the request
4
Response Handling
Results returned to AI agent with context preservation
Core MCP Platform Components
Natoma's MCP Hub serves as the orchestration layer between AI agents and enterprise systems:
MCP Gateway Layer
Request routing and load balancing
Protocol translation and optimization
Security enforcement and rate limiting
MCP Server Management
Lifecycle management for 100+ MCP servers
Auto-scaling based on AI agent demand
Version control and rollback capabilities
Enterprise Integration
OAuth 2.1 and SAML authentication
RBAC for AI agent permissions
Audit logging and compliance reporting
Hundreds of verified MCP servers,
ready to use.
Learn more about Natoma and the MCP ecosystem
Frequently-Asked Questions
What is an AI agent platform?
How does Natoma compare to Zapier MCP?
What is MCP discovery and why does it matter?
What is the difference between hosted and desktop MCP servers?
How does Natoma integrate with SIEM platforms?
Can Natoma enforce data loss prevention (DLP) policies?
How does Natoma provide visibility into AI tool usage?
Can Natoma deploy MCP servers on-premises?