Wanaku - A MCP Router that connects everything
LocalAbout Wanaku - A MCP Router that connects everything
Wanaku is a governed execution proxy for AI agents, positioned between agents and backend systems. It mediates tool calls, agent messages, and inference traffic, with policy controls and discovery of tools from upstream MCP servers.
Key features
- 01Isolates agents from backend systems
- 02Evaluates policies and intercepts tool calls
- 03Provides authentication and authorization
- 04Discovers tools from upstream MCP servers
- 05Separates namespaces by team or environment
- 06Dashboard for tools, resources, and prompts
Use cases
- 01Apply access policies before actions reach backends
- 02Publish Apache Camel routes as callable tools
- 03Organize tools and resources by team, tenant, or environment
- 04Manage tools and forwards through the dashboard
MCP support
Wanaku intercepts and governs MCP tool calls and can discover tools from upstream MCP servers. It provides MCP clients with a policy-controlled path for invoking tools.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEWanaku — A Governed Action Proxy for AI Agents
Wanaku is a governed action proxy for AI agents. It sits between agents and the systems they act on, intercepting Model Context Protocol (MCP) tool calls, agent-to-agent messages, and inference traffic. Before version 0.2.0, the project was named Wanaku MCP Router. It was renamed to Wanaku Governed Execution Proxy to reflect its expanded scope.
Wanaku supports open standards for AI agents and provides first-class integration with enterprise frameworks, including Apache Camel and Quarkus. For example, integration developers build Apache Camel routes and use Wanaku's Camel Integration Capability to publish them as tools. Agents call those tools with parameters, but Wanaku runs the work. Agents never access backend systems directly. The proxy enforces policy, identity, data controls, and audit requirements.
The project name comes from the origin of guanaco, a camelid native to South America.
Key Features
- Agent Isolation — Agents call tools through Wanaku; they never reach backend systems directly
- Policy Enforcement — LLM-powered evaluators + WASM action scripts classify, filter, and block tool calls in the proxy layer
- Identity & Auth — Authentication and authorization via oauth2-proxy and Keycloak, enforced before actions reach backends
- Tool Discovery — Auto-discover tools from upstream MCP servers; integration developers publish Camel routes as tools
- Namespace Isolation — Organize tools and resources across isolated namespaces per team, tenant, or environment
- Extensible Architecture — Plugin system via feature crates and a composable filter pipeline
- Admin Dashboard — Web UI for managing tools, resources, prompts, and forwards
- Container-Ready — Multi-arch images (x86_64, aarch64) published automatically
Quick Start
Install
Download the latest early-access build on Linux or macOS. Early-access builds are development builds of the unreleased Wanaku 0.3.0, the first stable release of this server. If you need a slower cadence of changes, watch the releases page for it.
curl -fsSL https://raw.githubusercontent.com/wanaku-ai/wanaku/main/get-wanaku.sh | bash
The installer detects the host platform, verifies the release checksum, and installs wanaku-server into $HOME/bin.
Override the destination with WANAKU_INSTALL_DIR. To run Wanaku in a container or as a systemd service, read the Getting Started guide.
Run wanaku-server and access http://localhost:8080 to enter the dashboard:

If you prefer a text interface, you may also download and use the Wanaku CLI from the Wanaku Barn project.
Learn Wanaku
The easiest way to learn Wanaku is by following the guided tutorial.
The reference documentation, including the complete installation and configuration instructions, is available in the usage guide.
Documentation
The Wanaku Documentation website contains the full project documentation.
Contributors working on the project may want to refer to the development documentation:
- Getting Started - Development setup guide
- Architecture - System architecture and components
- Configuration - Environment variables and configuration reference
- Management API - API reference
- Admin UI - Admin dashboard development
- Features / Plugins - Feature crate system
- Plugin Catalog - Publish and configure available UI plugins
- Plugin Development - Guide for writing new feature crates
- Evaluator Engine - WASM-based evaluator
- Action Policies - Deterministic MCP action rules
- Governance Posture - Enforcement modes and fail-safe behavior
- Contributing - Contribution guidelines
- Security - Security policy
Community
- GitHub Issues - Bug reports and feature requests
- Discussions - Ask questions and share ideas
Related Projects
- Wanaku Barn — Utilities for the Wanaku project: OpenShift/Kubernetes operator, CLI client, etc
- Camel Integration Capability — Build Apache Camel routes and publish them as tools that agents can call through Wanaku
License
This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.