feat(ai-gateway): Align AI landing pages with AI GW 2.0 model

app/_indices/ai-gateway.yaml

@@ -78,7 +78,7 @@ sections:
       - path: /ai-gateway/ai-providers/**/*
   - title: MCP traffic gateway
     items:
-      - path: /mcp/
+      - path: /ai-gateway/mcp/
       - title: Secure MCP traffic
         description: Secure GitHub MCP Server traffic with Kong Gateway and {{site.ai_gateway}}
         url: /mcp/secure-mcp-traffic/

app/_landing_pages/ai-gateway/a2a.yaml

@@ -27,7 +27,7 @@ rows:
             config: |
               The [Agent-to-Agent (A2A)](https://a2aproject.github.io/A2A/) protocol defines how AI agents communicate with each other over HTTP using JSON-RPC and REST bindings. As agent-to-agent communication moves into production, teams need visibility into A2A traffic and control over how it flows.
 
-              {{site.ai_gateway}} can act as a transparent proxy for A2A traffic. The [AI A2A Proxy](/plugins/ai-a2a-proxy/) plugin auto-detects A2A requests, extracts task metadata, rewrites agent card URLs, and feeds structured metrics into the Konnect analytics pipeline and [OpenTelemetry](/plugins/opentelemetry/) tracing.
+              {{site.ai_gateway}} acts as a control and observability layer for A2A traffic, enabling you to route agent-to-agent requests, extract task metadata, rewrite agent card URLs, and feed structured metrics into the Konnect analytics pipeline. In {{site.ai_gateway}} {% new_in 2.0 %}, you configure A2A traffic using [AI Agents](/ai-gateway/entities/ai-agent/) and attach [AI Policies](/ai-gateway/entities/ai-policy/) for authentication, access control, and observability.
 
       - blocks:
           - type: image
@@ -41,55 +41,52 @@ rows:
             config:
               header:
                 type: h2
-                text: "Proxy A2A Traffic"
+                text: "Proxy A2A traffic via {{site.ai_gateway}} {% new_in 2.0 %}"
               blocks:
                 - type: text
                   text: |
-                    The AI A2A Proxy plugin records A2A protocol metadata so you can analyze how agent-to-agent requests are processed.
+                    Create [AI Agent](/ai-gateway/entities/ai-agent/) entities to proxy your A2A endpoints through {{site.ai_gateway}} to unlock observability into agent communication.
+          - type: card
+            config:
+              icon: /assets/icons/linked-services.svg
+              title: AI Agent entity
+              description: Proxy A2A traffic using the AI Agent in {{site.ai_gateway}}.
+              ctas:
+                - text: AI Agent reference
+                  url: "/ai-gateway/entities/ai-agent/"
+                - text: AI Policy reference
+                  url: "/ai-gateway/entities/ai-policy/"
       - blocks:
           - type: structured_text
             config:
               header:
-                type: h4
-                text: "Secure A2A endpoints"
+                type: h2
+                text: "Secure and govern A2A traffic"
               blocks:
                 - type: text
                   text: |
-                    The AI A2A Proxy plugin handles A2A protocol concerns independently of authentication. Apply any {{site.base_gateway}} authentication plugin to the same service or route to secure your A2A endpoints.
-
-  - columns:
-      - blocks:
-          - type: card
-            config:
-              icon: /assets/icons/ai.svg
-              title: Proxy and observe A2A traffic
-              description: |
-                Export A2A metrics and traces with the AI A2A Proxy plugin and OpenTelemetry.
-              ctas:
-                - text: AI A2A Proxy plugin overview
-                  url: "/plugins/ai-a2a-proxy/"
-                - text: Proxy A2A agents through AI Gateway
-                  url: "/how-to/proxy-a2a-agents/"
-      - blocks:
+                    Secure access to your A2A agents by attaching [AI Policies](/ai-gateway/entities/ai-policy/) to your [AI Agent](/ai-gateway/entities/ai-agent/) entities for authentication and traffic control.
           - type: card
             config:
               icon: /assets/icons/lock.svg
-              title: Secure A2A endpoints
-              description: Apply authentication to A2A routes using standard gateway plugins.
+              title: Secure and govern with Policies
+              description: Secure A2A agents and control access with Policies.
               ctas:
-                - text: Secure A2A endpoints with OpenID Connect and Okta
-                  url: "/how-to/secure-a2a-endpoints-with-oidc/"
-                - text: Secure A2A endpoints with Key Authentication
-                  url: "/how-to/secure-a2a-endpoints/"
+                - text: OpenID Connect
+                  url: "/plugins/openid-connect/"
+                - text: Rate Limiting
+                  url: "/plugins/?category=traffic-control"
+                - text: Authentication plugins
+                  url: "/plugins/?category=authentication"
 
   - header:
       type: h2
-      text: "A2A traffic observability"
+      text: "Observe A2A traffic"
       description: |
         {{site.ai_gateway}} records A2A protocol traffic data so you can analyze how agent-to-agent requests are processed and resolved.
         - Audit logs capture task IDs, JSON-RPC method calls, payloads, latencies, and errors.
         - OpenTelemetry spans record task state, context IDs, TTFB, SSE event counts, and response sizes.
-        - Log plugins (File Log, HTTP Log, TCP Log, and others) consume the structured `ai.a2a` namespace emitted by the AI A2A Proxy plugin.
+        - Metrics track A2A-specific signals and performance indicators over time.
     column_count: 3
     columns:
       - blocks:
@@ -101,15 +98,6 @@ rows:
             cta:
               url: /ai-gateway/ai-audit-log-reference/#ai-a2a-proxy-logs
               align: end
-      - blocks:
-        - type: card
-          config:
-            title: Logging plugins
-            description: Send A2A traffic data to File Log, HTTP Log, TCP Log, and other destinations.
-            icon: /assets/icons/audit.svg
-            cta:
-              url: /plugins/?category=logging
-              align: end
       - blocks:
         - type: card
           config:
@@ -138,38 +126,14 @@ rows:
               url: /observability/explorer/?tab=agentic-usage#metrics
               align: end
 
-  - header:
-      type: h2
-      text: "Govern A2A traffic"
-      description: |
-        Use {{site.base_gateway}} plugins to control how A2A traffic flows through the gateway. 
-        Rate limiting, traffic control, and request transformation plugins work with A2A routes the same way they work with any other proxied traffic.         
-    column_count: 2
-    columns:
-      - blocks:
-        - type: card
-          config:
-            title: Rate limit A2A traffic
-            description: Apply rate limiting to A2A routes using standard gateway plugins.
-            cta:
-              url: /how-to/rate-limit-a2a-traffic/
-              align: end
-      - blocks:
-        - type: card
-          config:
-            title: Limit A2A request size
-            description: Use the Request Size Limiting plugin to restrict the size of A2A requests and responses
-            cta:
-              url: /how-to/limit-a2a-request-size/
-              align: end
-  - header:
-      type: h2
-      text: A2A how-to guides
-    columns:
-      - blocks:
-          - type: how_to_list
-            config:
-              tags:
-                - a2a
-              quantity: 5
-              allow_empty: true
+  # - header:
+  #     type: h2
+  #     text: A2A how-to guides
+  #   columns:
+  #     - blocks:
+  #         - type: how_to_list
+  #           config:
+  #             tags:
+  #               - a2a
+  #             quantity: 5
+  #             allow_empty: true

app/_landing_pages/ai-gateway/mcp.yaml

@@ -0,0 +1,148 @@
+metadata:
+  title: "MCP Traffic Gateway"
+  content_type: landing_page
+  description: This page is an introduction to MCP Traffic Gateway capabilities in {{site.ai_gateway}}.
+  products:
+    - ai-gateway
+    - gateway
+  works_on:
+    - on-prem
+    - konnect
+  breadcrumbs:
+    - /ai-gateway/
+  tags:
+    - ai
+    - mcp
+
+
+rows:
+  - header:
+      type: h1
+      text: "A trust and control layer for proxying traffic to MCP servers"
+      sub_text: Gain control and visibility over AI agent infrastructure with {{site.ai_gateway}}-driven MCP capabilities
+
+  - header:
+      type: h2
+      text: Bring MCP servers to production securely with {{site.ai_gateway}}
+    columns:
+      - blocks:
+          - type: text
+            config: |
+              AI agents are rapidly becoming core components of modern software, driving the need for structured, reliable interfaces to access tools and data. The Model Context Protocol (MCP) addresses this by enabling agents to reason, plan, and act across services. However, scaling MCP in remote, distributed environments introduces new operational challenges.
+
+              {{site.ai_gateway}} enables teams to manage remote MCP traffic with enterprise-grade security, performance, authentication, context propagation, load balancing, and observability. In {{site.ai_gateway}} {% new_in 2.0 %}, you configure MCP traffic using [AI MCP Servers](/ai-gateway/entities/ai-mcp-server/) and attach [AI Policies](/ai-gateway/entities/ai-policy/) for authentication, access control, and observability.
+
+              Learn how to:
+              - [Create MCP servers from API specs](#create-mcp-servers-from-api-specs-new-in-2-0)
+              - [Secure and govern MCP servers](#secure-and-govern-mcp-servers)
+              - [Observe MCP traffic](#observe-mcp-traffic)
+      - blocks:
+          - type: image
+            config:
+              url: /assets/images/gateway/mcp-architecture.svg
+              alt_text: Overview of AI gateway
+
+  - columns:
+      - blocks:
+          - type: structured_text
+            config:
+              header:
+                type: h2
+                text: "Generate MCP servers from API specs {% new_in 2.0 %}"
+              blocks:
+                - type: text
+                  text: |
+                    Turn any API into an MCP server using the [AI MCP Server](/ai-gateway/entities/ai-mcp-server/) entity. This approach does not require an LLM and provides full control over production workloads.
+
+                    The AI MCP Server entity:
+                    - Converts API schemas into MCP-compatible tool definitions
+                    - Aggregates multiple APIs into a single MCP server endpoint
+                    - Supports serverless deployments for dynamic tool generation
+                    - Integrates with AI assistants like Claude Desktop and other MCP clients
+          - type: card
+            config:
+              icon: /assets/icons/linked-services.svg
+              title: AI MCP Server entity
+              description: Generate an AI MCP Server from an API spec to expose tools and services over MCP in {{site.ai_gateway}}.
+              ctas:
+                - text: AI MCP Server reference
+                  url: "/ai-gateway/entities/ai-mcp-server/"
+                - text: AI Policy reference
+                  url: "/ai-gateway/entities/ai-policy/"
+      - blocks:
+          - type: structured_text
+            config:
+              header:
+                type: h2
+                text: "Secure and govern MCP servers"
+              blocks:
+                - type: text
+                  text: |
+                    Attach [AI Policies](/ai-gateway/entities/ai-policy/) to your [AI MCP Server](/ai-gateway/entities/ai-mcp-server/) entities to apply security, governance, and observability controls across your MCP infrastructure.
+
+                    Use AI Policies and Kong Gateway plugins to:
+                    - Secure access with the MCP OAuth2 policy or other authentication methods
+                    - Monitor MCP traffic using AI metrics and AI audit logs
+                    - Enforce access controls for MCP tool usage
+                    - Govern usage with rate limiting and traffic control plugins
+          - type: card
+            config:
+              icon: /assets/icons/lock.svg
+              title: Security and governance with Policies
+              description: Secure MCP servers and govern traffic with AI Policies.
+              ctas:
+                - text: MCP OAuth2 policy
+                  url: "/ai-gateway/entities/ai-policy/"
+                - text: Rate Limiting
+                  url: "/plugins/rate-limiting/"
+                - text: Observability
+                  url: "/ai-gateway/ai-audit-log-reference/#ai-mcp-logs"
+
+  - header:
+      type: h2
+      text: "Observe MCP traffic"
+    columns:
+      - blocks:
+          - type: structured_text
+            config:
+              blocks:
+                - type: text
+                  text: |
+                    {{site.ai_gateway}} records detailed Model Context Protocol (MCP) traffic data so you can analyze how requests are processed and resolved.
+                    - Logs capture session IDs, JSON-RPC method calls, payloads, latencies, and errors.
+                    - Metrics track latency, response sizes, and error counts over time, giving you a complete view of MCP server performance and behavior.
+  - columns:
+      - blocks:
+        - type: card
+          config:
+            title: MCP traffic audit log
+            description: Learn about {{site.ai_gateway}} logging capabilities for MCP traffic.
+            cta:
+              url: /ai-gateway/ai-audit-log-reference/#ai-mcp-logs
+              align: end
+      - blocks:
+        - type: card
+          config:
+            title: MCP traffic metrics
+            description: Expose and visualize LLM metrics for MCP traffic.
+            cta:
+              url: /ai-gateway/monitor-ai-llm-metrics/#mcp-traffic-metrics
+              align: end
+
+  - header:
+      type: h2
+      text: "MCP Registry (tech preview)"
+    columns:
+      - blocks:
+          - type: structured_text
+            config:
+              blocks:
+                - type: text
+                  text: |
+                    You can catalog your MCP servers in {{site.konnect_short_name}} {{site.konnect_catalog}}.
+                    This provides an internal catalog in {{site.konnect_short_name}} of your MCP servers.
+          - type: button
+            config:
+              text: "Enable MCP Registry in {{site.konnect_short_name}} Labs"
+              url: /catalog/mcp-registry/
+

app/_redirects

@@ -367,3 +367,7 @@
 # Spec renames
 /api/konnect/api-builder/v3/ /api/konnect/api-catalog/v3/   301
 /api/konnect/api-builder/ /api/konnect/api-catalog/   301
+
+# MCP landing page
+
+/mcp/ /ai-gateway/mcp/

app/ai-gateway/load-balancing.md

@@ -33,13 +33,13 @@ related_resources:
 
 {{site.ai_gateway}} provides load balancing capabilities to distribute requests across multiple LLM models. You can use these features to improve fault tolerance, optimize resource utilization, and balance traffic across your AI systems.
 
-In {{site.ai_gateway}} 2.0.0 and later, load balancing is configured on the [Model entity](/ai-gateway/entities/ai-model/) through `config.balancer` and `target_models`.
+In {{site.ai_gateway}} {% new_in 2.0 %}, load balancing is configured on the [Model entity](/ai-gateway/entities/ai-model/) through `config.balancer` and `target_models`.
 
 <!-- Commented out for future reference - Compatibility with existing configurations
 {:.info}
-> With {{site.ai_gateway}} 2.0, both configuration approaches can appear in existing deployments:
+> With {{site.ai_gateway}}, both configuration approaches can appear in existing deployments:
 > - Legacy plugin-based approach: configure load balancing directly on [AI Proxy Advanced](/plugins/ai-proxy-advanced/) plugin instances.
-> - {{site.ai_gateway}} 2.0 approach: configure load balancing on the [Model entity](/ai-gateway/entities/ai-model/) with `config.balancer` and `target_models`.
+> - {{site.ai_gateway}} approach: configure load balancing on the [Model entity](/ai-gateway/entities/ai-model/) with `config.balancer` and `target_models`.
 >
 > For new {{site.ai_gateway}} deployments, use the Model entity workflow.
 -->