Wanaku
The Wanaku MCP Router stands between autonomous AI agents and your enterprise systems. Wanaku leverages proven integration technology, like Apache Camel, to set up and manage hundreds or thousands of integrations.
What is Wanaku?
Wanaku is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to wanaku mcp router stands between autonomous ai agents and your enterprise systems. wanaku leverages proven integration technology, like apache camel, to set up and manage hundreds or thousands of inte...
The Wanaku MCP Router stands between autonomous AI agents and your enterprise systems. Wanaku leverages proven integration technology, like Apache Camel, to set up and manage hundreds or thousands of integrations.
This server falls under the Cloud Services category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- The Wanaku MCP Router stands between autonomous AI agents an
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx wanaku-mcp-serverConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Wanaku
Wanaku is an enterprise MCP Router that positions itself between autonomous AI agents and your internal systems, providing centralized governance and routing for AI tool calls at scale. Built on Apache Camel, it supports 400+ pre-built integration components covering databases, messaging systems, REST APIs, and cloud services. Organizations use Wanaku to manage hundreds or thousands of integrations from a single control plane, avoiding the operational complexity of deploying separate MCP servers for each enterprise backend.
Prerequisites
- Java runtime (JVM) installed on the host machine
- Wanaku CLI binary downloaded from https://github.com/wanaku-ai/wanaku/releases
- An MCP-compatible AI client such as Claude Desktop or Cursor
- Optional: Keycloak for authentication (Wanaku runs without auth by default)
Download and install the Wanaku CLI
Download the latest Wanaku CLI release for your platform from the GitHub releases page. Unpack the archive and move the binary to a directory on your PATH so it can be executed from anywhere.
# Download from https://github.com/wanaku-ai/wanaku/releases
tar -xzf wanaku-cli-*.tar.gz
mv wanaku /usr/local/bin/
wanaku --versionStart the Wanaku router
Launch Wanaku in local mode. This starts the MCP router and exposes the management dashboard at http://localhost:8080 where you can register integrations.
wanaku start localAccess the management dashboard
Open http://localhost:8080 in your browser to access the Wanaku dashboard. Use it to organize tools into namespaces and configure Apache Camel routes to backend enterprise systems.
Register integration endpoints
Add tools and resources through the dashboard or CLI. Each entry defines an Apache Camel route that connects to a specific backend — such as a database query, a REST API call, or a message queue producer.
Configure your MCP client to connect to Wanaku
Add Wanaku to your MCP client configuration. All registered tools are automatically exposed to the AI agent through the router.
{
"mcpServers": {
"wanaku": {
"command": "wanaku",
"args": ["start", "local"]
}
}
}Follow the guided tutorial
The Wanaku documentation recommends starting with the guided tutorial at https://wanaku.ai/docs and the wanaku-examples repository to learn how to configure your first end-to-end integration.
Wanaku Examples
Client configuration
Connect Claude Desktop or another MCP client to the locally running Wanaku router. The router serves all registered integration tools over MCP.
{
"mcpServers": {
"wanaku": {
"command": "wanaku",
"args": ["start", "local"]
}
}
}Prompts to try
Once Wanaku is running with integrations registered, these prompts demonstrate how AI agents interact with connected enterprise systems.
- "Show all tools currently registered in the Wanaku router"
- "Query the inventory database for items with stock below 10 units"
- "Post a notification to the ops Kafka topic that deployment has completed"
- "Call the internal HR REST API to get the headcount for the engineering department"Troubleshooting Wanaku
Wanaku fails to start and reports a port conflict on 8080
Another service is using port 8080. Stop the conflicting service or configure Wanaku to use a different port. Check the Wanaku documentation for port configuration options.
MCP client does not see any tools after connecting to Wanaku
Ensure at least one tool or resource has been registered in the Wanaku dashboard. Tools are only visible to agents after they are explicitly added to a namespace through the dashboard or CLI.
Apache Camel route fails with a connection error to the backend system
Verify network connectivity from the Wanaku host to the target backend. Check the Camel component configuration (credentials, hostnames, ports) in the dashboard and review Wanaku logs for detailed error messages.
Frequently Asked Questions about Wanaku
What is Wanaku?
Wanaku is a Model Context Protocol (MCP) server that wanaku mcp router stands between autonomous ai agents and your enterprise systems. wanaku leverages proven integration technology, like apache camel, to set up and manage hundreds or thousands of integrations. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Wanaku?
Follow the installation instructions on the Wanaku GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Wanaku?
Wanaku works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Wanaku free to use?
Yes, Wanaku is open source and available under the Apache-2.0 license. You can use it freely in both personal and commercial projects.
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