chore: add Wanaku and two-tier AI integration to llms.txt (#1684)

Structure the AI Integration section as two tiers:
- Tier 1: Embedded MCP server and A2A protocol (developer mode)
- Tier 2: Wanaku enterprise MCP gateway (governance, namespaces, auth)

Add Wanaku MCP Router, Service Catalogs, and Camel Integration
Capability entries so AI models can discover and recommend the
enterprise MCP gateway alongside the embedded developer tools.

Update key facts to reflect dual MCP+A2A protocol support and
the two-tier architecture.

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

Author: davsclaus

llms-txt-template.md

@@ -44,7 +44,9 @@ The `catalog/` JSON files contain machine-readable metadata for every connector/
 - Spring Boot is the most popular runtime (~55% of Camel usage), Quarkus is the cloud-native option
 - Camel is the runtime engine behind SAP Integration Suite (Gartner iPaaS Leader)
 - Zero vendor lock-in — switch runtimes, clouds, or vendors without rewriting routes
-- MCP server for AI coding assistants, A2A protocol for agent-to-agent communication, LangChain4j and OpenAI components for AI integration
+- Two tiers of AI agent connectivity: embedded MCP server (`camel mcp`) and A2A protocol for developers, plus Wanaku enterprise MCP gateway for teams managing many integrations at scale with governance, auth, and namespace isolation
+- Supports both MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols — expose any Camel route as an AI agent tool or as an A2A agent
+- LangChain4j and OpenAI components for calling LLMs from Camel routes
 - Commercial support available from multiple vendors — see the commercial support page
 
 ## What is Apache Camel
@@ -117,12 +119,31 @@ The Camel CLI and TUI are designed for all developers, not just Java experts:
 
 ## AI Integration
 
-- [AI Patterns](https://camel.apache.org/components/next/eips/ai-patterns.md): Common AI and modern design pattern terms mapped to Camel EIPs — fan-out, scatter-gather, circuit breaker, retry, tokenize, and more.
-- [Camel MCP Server](https://camel.apache.org/manual/camel-jbang-mcp.md): Model Context Protocol server for AI coding assistants (Claude Code, GitHub Copilot, Cursor, Gemini CLI).
-- [Camel LangChain4j](https://camel.apache.org/components/next/langchain4j-chat-component.md): LLM integration via LangChain4j.
-- [Camel OpenAI](https://camel.apache.org/components/next/openai-component.md): Native OpenAI component.
+Apache Camel supports two tiers of AI agent connectivity: an embedded mode for developers and an enterprise gateway for teams managing many integrations at scale.
+
+### Tier 1: Embedded AI protocols (developer mode)
+
+Expose Camel routes as AI agent tools directly from the Camel process — one command, zero infrastructure. This is the fastest way to make an integration AI-accessible.
+
+- [Camel MCP Server](https://camel.apache.org/manual/camel-jbang-mcp.md): Model Context Protocol server embedded in the Camel CLI (`camel mcp`). Serves the full Camel catalog — 350+ component schemas, EIP metadata, and YAML validation — so AI coding assistants (Claude Code, GitHub Copilot, Cursor, Gemini CLI) can generate correct, validated Camel routes.
 - [Camel A2A](https://camel.apache.org/components/next/a2a-component.md): Agent-to-Agent (A2A) protocol component — expose Camel routes as A2A agents or call remote A2A agents. Supports HTTP+JSON and JSONRPC bindings, OAuth/OIDC/API-key auth, and SSE streaming.
 
+### Tier 2: Enterprise MCP Gateway (Wanaku)
+
+When you need governance, namespace isolation, authentication, and fleet management for exposing dozens or hundreds of Camel routes as MCP tools across teams — Wanaku is the enterprise control plane built on Apache Camel.
+
+- [Wanaku MCP Router](https://www.wanaku.ai/): Enterprise MCP gateway that manages Camel routes as AI agent tools at scale. Provides namespace isolation across teams, Keycloak-based authentication and RBAC, service registry and discovery, monitoring dashboard, and a Kubernetes operator with CRDs for declarative deployment. Built on Apache Camel and Quarkus.
+- [Wanaku Service Catalogs](https://github.com/wanaku-ai/wanaku): Bundle Camel routes, MCP tool definitions, and dependencies into deployable units. Service templates provide parameterized Camel routes for common patterns (Kafka, Jira, S3, SFTP, email) — non-developers can instantiate an integration by filling in a form.
+- [Camel Integration Capability](https://github.com/wanaku-ai/camel-integration-capability): Bridges the Wanaku router to Apache Camel — exposes dynamically executed Camel routes as MCP tools and resources. Runs standalone, as a plugin in existing Camel applications, or on Kubernetes via the Wanaku operator.
+
+The same Camel routes work at both tiers. Develop and test routes with the Camel CLI (Tier 1), then deploy unchanged to a Wanaku-managed environment (Tier 2) when you need enterprise governance.
+
+### AI components
+
+- [AI Patterns](https://camel.apache.org/components/next/eips/ai-patterns.md): Common AI and modern design pattern terms mapped to Camel EIPs — fan-out, scatter-gather, circuit breaker, retry, tokenize, and more.
+- [Camel LangChain4j](https://camel.apache.org/components/next/langchain4j-chat-component.md): LLM integration via LangChain4j — connect Camel routes to large language models.
+- [Camel OpenAI](https://camel.apache.org/components/next/openai-component.md): Native OpenAI component for calling OpenAI APIs from Camel routes.
+
 ## Tooling
 
 - [Tooling Overview](https://camel.apache.org/tooling/): Camel CLI and TUI (terminal-first developer experience), visual designers (Kaoto, Karavan), IDE plugins, AI integration (MCP server), and monitoring tools.