Kong Launches Context Mesh to Connect Enterprise Data to AI Agents

Kong Context Mesh transforms existing APIs into agent-ready tooling, addressing the integration gap that threatens agentic AI initiatives

Kong Inc., a leading developer of API and AI connectivity technologies, announced Kong Context Mesh, an industry-first product that can automatically discover enterprise APIs, transform them into agent-consumable tooling, and deploy those tools with runtime governance. This new offering is the latest for Kong’s AI Connectivity platform, which along with MCP Registry, AI Gateway, and Event Gateway, positions Kong as the only platform that can discover, generate, deploy, and govern agent tooling across the full AI data path.

“Organizations have spent years building APIs as the nervous system of the enterprise. Context Mesh allows them to reuse that investment to power agents instead of starting from scratch,” said Marco Palladino, CTO and Co-Founder of Kong Inc. “The challenge is that agents are only as good as the enterprise context they can reach. And this is what AI Connectivity is meant to provide: a governed and secure flow of intelligence between models, applications, and data. Our goal is to help customers move from experimenting with agents to operating them reliably at scale on the platforms they already trust.”

The Agent Problem
The promise of agentic AI depends on controlled IT access, because agents will need real-time access to enterprise data, as well as the ability to invoke governed capabilities within existing systems. However, enterprise context is scattered across APIs, event streams, and applications, each with different schemas, credentials, and access rules. Initially, connecting agents to this IT landscape has required manual integration for every source, slowing projects and increasing risk.

Recent industry research has highlighted the need for a new integration pattern that enables agents to securely discover state, reason across systems, and initiate actions in real time. Without this bridge, many agent initiatives will struggle to reach production. Kong Context Mesh is designed to help close that gap by turning existing API infrastructure into agent-ready connectivity. In their January 2026 report “How to Enable Agentic AI via API-based Integration,” Gartner® analysts identified this challenge, writing that “a new integration model is required, one that establishes a real-time context mesh, enabling agents to securely discover state, reason across systems, and trigger actions seamlessly within and across platforms.” The report warns that “failure to bridge this integration gap puts 40% of agentic AI initiatives at risk of cancellation by 2027.”

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How Context Mesh Works
Context Mesh uses knowledge that the Kong Konnect platform already maintains about customers’ environments, including endpoints, schemas, authentication requirements, and policies, to automate agent integration:

• Automatic Discovery reveals every API under management in the Kong Konnect platform without manual inventory
• Curated Toolkits allow teams to select precise context for specific agents
• Instant MCP Generation creates fully functional Model Context Protocol (MCP) tool definitions with correct schemas and built-in authentication
• Gateway Deployment publishes generated tooling directly to Kong AI Gateway with policies enforced at runtime
• Inherited Access Controls automatically extend existing Kong security to agent tooling
• Policy Enforcement can define conditional policies and orchestration logic, including rate limiting, conditional routing, and data transformation
• Integration with MCP Registry registers and catalogs generated MCP servers and compose tools

Every toolkit generated through Context Mesh is registered in the Kong Konnect MCP Registry for enterprise-wide discovery and reuse, giving developers a single place to find both APIs and agent tools.

Potential Business Impact
By eliminating manual integration work, Kong Context Mesh can help organizations:

• Reduce weeks of API inventory and mapping effort
• Accelerate delivery of agentic applications
• Enforce consistent security across human and machine consumers
• Lower operational cost by reusing existing Kong infrastructure
• Protect prior API investments while moving to AI-first architectures