The MarcoPolo Model Context Server is a data integration runtime for AI agents that provides Engineering leaders and AI Architects with the peace of mind to scale AI safely across the enterprise. It is a secure layer that replaces integration sprawl, eliminates model context overload and closes the governance gap.


As AI reasons over enterprise data, it relies on a growing web of MCP servers, APIs, and one-off integrations. Without a bounded data execution environment that maintains memory and state, integration paths fragment, making agentic AI increasingly complex, fragile and difficult to scale.

Agentic AI require rich context to reason effectively, but injecting documents and code into prompts introduces noise, drives up token costs, and leads to inconsistent outcomes. Without a structured semantic context layer, reasoning quality degrades, leading to hallucinations and inconsistent answers.

Existing role based access controls were built for human users with predictable intent. Agentic AI operates autonomously across systems, executing actions with dynamic intent. Without intent-based governance and auditability, enterprises lack the ability to safely control, monitor and explain agent behavior.
MarcoPolo sits between your AI agents and enterprise data sources, providing unified tools, secure execution and governance.
How it works
Develop freely on your own and unlock all features when your team needs to scale.

AI-first builders working with internal data.
Consumption-based pricing

Designed for enterprise security and governance.
Platform fees + consumption-based pricing
Give developers and operations teams speed and agility without added complexity.
Enable AI that reasons across systems to deliver accurate, cross-silo intelligence.
Enterprise-grade security and governance built in, not bolted on.

Connect to live systems in minutes, run tools safely, and give your LLM the context it needs to operate effectively.
