Wanaku 0.1.1: Scaling AI Agent Capabilities with Apache Camel and MCP

Bringing Apache Camel Integration Capabilities to AI Agents via MCP

Wanaku 0.1.1 is an open-source MCP router that bridges AI agents with enterprise systems. It utilizes Apache Camel as its first-class integration runtime to provide access to over 400 components.

Why This Matters

Exposing enterprise logic to AI agents typically requires building custom REST wrappers, manual tool definitions, and complex container orchestration for every new capability. By leveraging Apache Camel’s existing ecosystem of 400+ components and Enterprise Integration Patterns (EIPs), Wanaku replaces bespoke glue code with a declarative framework, reducing the friction of connecting LLMs to heterogeneous, protocol-diverse enterprise environments.

Key Insights

• • Service Catalogs (2026) bundle Camel routes, MCP tool definitions, and Maven dependencies into a single deployable package.
• • The ‘wanaku_body’ concept maps AI agent input directly into the Camel data exchange body, allowing routes to use ${body} in URIs.
• • Service Templates use Camel Property Placeholders ({{property}}) to create reusable blueprints for integrations like Kafka or JMS.
• • The Camel Integration Capability is a Java application using Apache Camel Main and the Wanaku Capabilities Java SDK to execute routes.

Working Examples

Apache Camel route definition for retrieving book info via ISBN using YAML DSL.

- route:
  id: get-book-by-isbn
  description: Retrieve book information by ISBN
  from:
    uri: direct:get-by-isbn
  steps:
    - setHeader:
        name: CamelHttpMethod
        constant: GET
    - log:
        message: "Fetching book with ISBN: ${body}"
    - toD:
        uri: "https://openlibrary.org/api/books?bibkeys=ISBN:${body}&format=json&jscmd=data"
    - convertBodyTo:
        type: String
    - log:
        message: "Book data received: ${body}"

Command to launch the Wanaku router and admin UI locally.

wanaku start local

Practical Applications

• • Legacy System Access: Using camel-ftp or camel-jms to allow AI agents to interact with systems lacking REST APIs; avoid custom API wrappers which increase maintenance overhead.
• • Cloud Storage Orchestration: Using camel-aws-s3 or camel-azure-files for agentic file management; avoid hardcoding cloud SDKs in agent logic which limits portability.

References:

• https://dev.to/orpiske/wanaku-011-bringing-apache-camel-integration-capabilities-to-ai-agents-via-mcp-1od5
• https://github.com/wanaku-ai/wanaku/releases/
• https://wanaku.ai/docs/demos/