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  4. From APIs to Agentic Integration: Introducing Kong Context Mesh
[Product Releases](/blog/product-releases)Product Releases
February 10, 2026
5 min read

# From APIs to Agentic Integration: Introducing Kong Context Mesh

Alex Drag
Head of Product Marketing

The promise of agentic AI is clear: autonomous systems that can reason, plan, and act on your behalf. But there's a fundamental problem standing between that vision and enterprise reality: agents need context to make decisions, and that context lives scattered across your organization.

Context is any data — or any abstraction that enables access to data — that an agent needs to do its job. Customer records in your CRM. Inventory levels behind your fulfillment APIs. Pricing rules in your commerce platform. Transaction streams flowing through your event infrastructure. It's the operational intelligence your business runs on, locked away in dozens of systems with different access patterns, authentication schemes, and data formats.

Today, we're announcing Kong Context Mesh, a new product that enables you to both design how agents consume the enterprise context they need and expose access to that context — automatically discovering your existing infrastructure, transforming it into agent-consumable tooling, and governing access with the controls enterprises require.

## The context problem

Agents are ultimately decision makers. They make those decisions by combining intelligence with context, ultimately meaning they are only ever as useful as the context they can access. An agent that can't check inventory levels, look up customer history, or verify pricing isn't autonomous — it's just a chatbot that sounds confident. The real value of agentic AI comes from connecting reasoning capabilities to the operational data and actions that drive your business.

But getting context to agents is harder than it sounds. Your enterprise data lives behind APIs, event streams, databases, and services — each with different schemas, authentication requirements, and access patterns. Someone needs to understand each data source, define how it should be exposed to agents, handle credentials, manage errors, and figure out how to host the resulting integration. Multiply that by the dozens of systems that hold the context agents need, and you've got a project that never ships — even as pressure to deliver agentic capabilities accelerates.

Meanwhile, Kong already knows about much of this infrastructure. It knows the endpoints, the schemas, the authentication requirements, and critically, it knows who has access to what. That context has been sitting there, waiting to be activated.

With Context Mesh, it’s activated.

## Kong Context Mesh: Tech Preview

Context Mesh solves the agent context problem by leveraging what Kong already knows about your infrastructure. With the tech preview release, we're starting with how MCP interacts with APIs — the most common abstraction layer for enterprise data — and expanding from there. Here's what you can do:

  • - **Discover what you have.** Context Mesh automatically surfaces every API currently under Kong management. No manual inventory. No spreadsheet archaeology. You see your complete API landscape in one place, with full visibility into endpoints, schemas, and access patterns.
  • - **Understand who can access what. **Because Kong already manages authentication and authorization for your APIs, Context Mesh knows exactly which data sources any given user or service has access to. This becomes the foundation for agent-appropriate access controls — you're not starting from scratch on permissions.
  • - **Curate your agent toolkit.** Not every data source belongs in every agent's toolbox. Context Mesh lets you filter across endpoints from different APIs and select precisely which context you want to expose. You're composing a purpose-built toolkit, not dumping your entire data landscape into an agent's context window.
  • - **Generate agent-ready tooling automatically.** Once you've selected your data sources, Context Mesh generates fully-functional tool definitions that agents can consume. The schemas are correct. The authentication is handled. The error responses are meaningful. What would take days of manual work happens in minutes. We're starting with MCP as the output format — it's where the ecosystem is converging — but the abstraction is designed to support however agents consume context as the landscape evolves.
  • - **Deploy to a Kong Gateway.** Generated tooling isn't an artifact you have to figure out how to host. Context Mesh deploys directly to any of your Kong AI Gateway environments to host your agent tooling and enforces policies at execution time. You get production-grade infrastructure from day one.
  • - **Define policies and orchestration logic.** Define conditional policies and logic that govern how these tools behave. Rate limiting, conditional routing, data transformation — the same governance patterns you've built for APIs now apply to your agent infrastructure, enforced by Context Runner at runtime.

## The vision: Full context coverage

The tech preview focuses on APIs because that's where most enterprises have the deepest existing investment in Kong. But agents need context from across the enterprise — not just what's behind REST endpoints. Our roadmap extends Context Mesh to wherever your data lives — and you can expect to see the following built over the course of the next year:

  • - **Event streams and real-time data as context for event-driven agents**. Don’t forget: last year, we released Kong Event Gateway to help you govern access to event data just like your do APIs. And agents need real-time context. So, Kong Context Mesh will discover the event data products under Kong management and enable you to filter across virtual clusters and turn event streams into agent-consumable tools — giving agents access to real-time context, not just point-in-time queries.
  • - **Unified toolkits.** Future releases will let you generate tooling that combines APIs and event streams in a single MCP server. An agent helping with order management could query the orders API and subscribe to inventory events, all through a coherent MCP toolkit you composed in minutes.
  • - **Connectors for direct data access. **We're building toward a world where Context Mesh can discover data from sources beyond your Kong-managed infrastructure — databases, SaaS platforms, file stores—and turn those connectors into agent tools. The boundary between "API" and "data source" dissolves. Agents get access to the context they need through a consistent, governed interface, regardless of where that context lives.

## Why this only works at Kong

Individual pieces of this vision exist elsewhere. You can find tool generators. You can find API catalogs. You can find identity management solutions. What you can't find is a platform where these capabilities compound.

  • - **Registry integration.** Every MCP toolkit and server you generate through Context Mesh can be cataloged in Kong's registry. This isn't a separate system to maintain; it's automatic. Your agent developers discover available tools through the same portal they use for APIs.
  • - **Inherited access controls.** Because Kong already knows which data sources any consumer should have access to, it automatically knows which agent tools that consumer can use. You don't rebuild your access model for agents; you extend the one you already have.
  • - **Portal-driven access requests.** Consumers can request access to agent tooling through the same developer portal and registration flow they use today. The experience is familiar. The governance is consistent. The audit trail is complete.
  • - **Identity as a foundation. **Kong Identity becomes your agent identity management solution. When you're defining policies and access controls in Context Mesh, you're referencing the same identity infrastructure that governs your entire connectivity layer. Agents authenticate the same way services do. Policies apply consistently across human and machine consumers.

## Getting started

Context Mesh and Context Runner both enter tech preview this quarter. If you're a Kong customer exploring agentic AI, [register for early access](https://konghq.com/lp/register-context-mesh-beta)register for early access. If you're evaluating how to connect your existing data infrastructure to the agents that will increasingly drive your business, this is the conversation to have.

The transition from API-first to agent-first doesn't require abandoning what you've built. It requires a platform that can bridge the two — discovering the context you have, transforming it into what agents need, and governing access with enterprise-grade controls.

That's what Kong Context Mesh delivers. And we're just getting started.

[Register for early access now!](https://konghq.com/lp/register-context-mesh-beta)Register for early access now!

- [Agentic AI](/blog/tag/agentic-ai)Agentic AI- [API Management](/blog/tag/api-management)API Management- [MCP](/blog/tag/mcp)MCP- [AI Gateway](/blog/tag/ai-gateway)AI Gateway- [Governance](/blog/tag/governance)Governance- [Microservices](/blog/tag/microservices)Microservices

Table of Contents

  • The context problem
  • Kong Context Mesh: Tech Preview
  • Why this only works at Kong
  • Getting started

## More on this topic

_Videos_

## Service Catalog: Unifying Discovery for API Consumers and Producers

_Videos_

## Agentic AI at Scale: AI Gateway + MCP Governance

## See Kong in action

Accelerate deployments, reduce vulnerabilities, and gain real-time visibility. 

[Get a Demo](/contact-sales)Get a Demo
**Topics**
- [Agentic AI](/blog/tag/agentic-ai)Agentic AI- [API Management](/blog/tag/api-management)API Management- [MCP](/blog/tag/mcp)MCP- [AI Gateway](/blog/tag/ai-gateway)AI Gateway- [Governance](/blog/tag/governance)Governance- [Microservices](/blog/tag/microservices)Microservices
Alex Drag
Head of Product Marketing

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