We're thrilled to announce that Kong, the AI connectivity company, has been recognized as a Leader in the Gartner Magic Quadrant for API Management for the seventh year in a row. Plus, Kong was positioned furthest on the Completeness of Vision axis for the third year in a row, among all 17 vendors evaluated.
We feel this ongoing recognition showcases how Kong continues to prove it's the connectivity layer built for the AI and agentic era. For teams building their AI and agentic architecture, we believe this year's report makes the case plainly: Kong is built for where that architecture is headed.
For architecture and platform leaders, this recognition provides a useful lens for evaluating an API management platform. Key criteria include governance, security, observability, scalability, deployment flexibility, and support for API and AI traffic across hybrid and multi-cloud environments.
As[ _defined by Gartner_](https://www.gartner.com/en/about/magic-quadrant-faq) _defined by Gartner_, the Gartner Magic Quadrant is a "visual tool backed by a rigorous methodology that provides a graphical comparative positioning of technology and service providers in a specific market." In it, Gartner evaluates vendors based on two criteria: Ability to Execute and Completeness of Vision.
Gartner defines Leaders as providing "mature offerings that meet market demand and have demonstrated the vision necessary to sustain their market position as requirements evolve."
Completeness of Vision includes "market understanding, marketing strategy, sales strategy, offering (product) strategy, business model, vertical/industry strategy, innovation and geographic strategy."
Ability to Execute includes “products/services, overall viability, sales execution/pricing, market responsiveness, marketing execution, customer experience and operations”
In our opinion, for enterprise buyers, Ability to Execute reflects current delivery, while Completeness of Vision signals how a vendor may address evolving requirements. Together, these dimensions can help leaders compare platform maturity with long-term architectural fit.
We believe this report captures the shift underway in the market, and that it shows Kong understands the shift from traditional API management to AI connectivity.
Our vision includes governing the full AI data path, with initiatives such as context mesh for agent context mediation, integrated machine-to-machine identity management, and capabilities for packaging and monetizing APIs, event streams, agents, LLMs, and MCP servers.
None of this was built to chase a quadrant cycle. AI Gateway, automated MCP server creation, Event Gateway, and Dedicated Cloud Gateways shipped because the market needed them — and we feel this year's scoring confirms what Kong has been building toward: **there's no AI success without governed connectivity**.
Kong’s unified platform enables organizations to secure, govern, accelerate, and monetize the flow of intelligence across AI and API traffic — on any model, any cloud.
[Get the full report](https://konghq.com/resources/reports/gartner-magic-quadrant-full-lifecycle-api-management)Get the full report to learn more, or [request a demo](https://konghq.com/contact-sales)request a demo to see it in action.
*Gartner, Magic Quadrant for API Management, 28 September 2026, By: Shameen Pillai, Nicholas Carter, John Santoro*
*Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates.*
*Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.*
**What does the Gartner Magic Quadrant measure?**
Gartner describes a Magic Quadrant as a methodology-backed visual tool for comparing technology and service providers within a defined market. It evaluates providers using Ability to Execute and Completeness of Vision, as explained in Gartner’s [_Magic Quadrant FAQ_](https://www.gartner.com/en/about/magic-quadrant-faq)_Magic Quadrant FAQ_.
**What do Leader and Completeness of Vision mean?**
Gartner defines Leaders as providers with mature offerings that meet market demand and a vision intended to sustain their position as requirements evolve. Completeness of Vision considers factors such as market understanding, product strategy, innovation, and geographic strategy. These designations describe Gartner’s market assessment; they are not a stack ranking or a universal recommendation for every buyer.
**What role does an API gateway play in API management?**
An API gateway is a reverse proxy that manages, configures, and routes API requests. Kong Gateway documents gateway-layer authentication, rate limiting, and monitoring and observability integrations. Within API management, these controls help teams apply consistent traffic policies at a shared control point. See the [_Kong Gateway documentation_](https://developer.konghq.com/gateway/)_Kong Gateway documentation_.
**How does Kong describe extending API management to AI and agentic traffic?**
In Kong AI Gateway 2.0’s documented hybrid architecture, self-managed data-plane nodes receive LLM, MCP, and A2A traffic and evaluate it against policies distributed by the Konnect-managed control plane, as described in the [_Kong AI Gateway architecture_](https://developer.konghq.com/ai-gateway/architecture/)_Kong AI Gateway architecture_. Kong documents five [_AI MCP Server modes_](https://developer.konghq.com/ai-gateway/entities/ai-mcp-server/)_AI MCP Server modes_ for different integration patterns. Depending on the selected mode, these include exposing REST APIs as discoverable MCP tools, proxying existing MCP servers with authentication and observability, and aggregating tools from multiple sources into one MCP endpoint.
**What should enterprise teams evaluate in an API management platform?**
Enterprise teams should evaluate governance, security, observability, scalability, deployment flexibility, lifecycle management, and support for API and AI traffic. They should also test architectural fit, operational ownership, regulatory requirements, and the platform’s ability to reduce duplicated controls across teams. Analyst research can inform this process, but product validation should reflect the organization’s own requirements.
**How does Kong support hybrid and multi-cloud API management?**
[_Kong Gateway_](https://developer.konghq.com/gateway/)_Kong Gateway_ is documented for hybrid and multi-cloud deployments. In hybrid mode, it separates control-plane and data-plane roles, and the [_Kong Gateway deployment topologies_](https://developer.konghq.com/gateway/deployment-topologies/)_Kong Gateway deployment topologies_ documentation describes data-plane groups across different data centers, geographies, or zones. Teams should verify product, feature, region, and operational support for their planned topology before making an architecture decision.
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