Wanaku
The first open-source MCP Router for secure, scalable AI agent integrations.
Wanaku is a promising open-source MCP Router for developers who need a secure, scalable bridge between AI agents and enterprise systems. Its recent SQL tool and GitHub integrations expand practical use cases, but its reliance on Apache Camel means a steeper learning curve for non-Java teams. Worth adopting if you value open-source flexibility and are building agentic workflows at scale.
- Developers building agentic AI applications
- Teams needing secure integration of LLMs with enterprise data
- Organizations scaling AI agent interactions across many endpoints
- Projects requiring open-source MCP routing with access control
- Non-technical users who require a no-code platform
- Teams looking for a commercial vendor with paid support
- Projects needing direct integration without a routing layer
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In short
Wanaku — The first open-source MCP Router for secure, scalable AI agent integrations. Best for Developers building agentic AI applications, Teams needing secure integration of LLMs with enterprise data, Organizations scaling AI agent interactions across many endpoints. Free to use.
What's new in Wanaku
Checked 13 days agoAcross the latest 3 updates: 2 feature updates and 1 changelog entry.
Building an MCP SQL Tool for LLMs with Wanaku and Apache Camel
New sql-tool service template connects AI assistants to live relational databases via MCP.
Wanaku 0.1.3 Released
0.1.3 adds GitHub tools, service template improvements, non-blocking MCP ops, Quarkus 3.33.2 upgrade.
Welcome to the New Wanaku Website
New website with homepage, blog, community page, and reorganized documentation launched.
Viability Score
How likely is Wanaku to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- MCP router for autonomous AI agents
- Access control and auditing enforcement
- Error handling for LLM interactions
- Expose enterprise resources as MCP tools
- Reusable tool sets (service templates)
- Pluggable architecture with Apache Camel
- Scalability to hundreds or thousands of endpoints
- CLI and UI for quick setup
- Support for HTTP, Kafka, FTP protocols
- Integration with 300+ Apache Camel components
- Custom capabilities via SDK
- Non-blocking MCP operations (since 0.1.3)
- GitHub tools integration (since 0.1.3)
- SQL tool service template for database queries
- Community-driven development
About Wanaku
Wanaku is an open-source MCP Router that serves as a smart intermediary between autonomous AI agents and enterprise systems. It automates repetitive integration configurations across multiple protocols including HTTP, Kafka, and FTP, while enforcing access control, auditing, and error handling. Built with Apache Camel and Quarkus, it scales to handle hundreds or thousands of endpoints, making it ideal for developers building agentic applications. Wanaku provides a CLI and UI for quick setup, allowing users to expose enterprise resources as MCP tools and expand via reusable tool sets. Its pluggable architecture supports custom capabilities through an SDK, and recent updates include a new SQL tool service template for connecting AI assistants to relational databases, as well as GitHub tools integration. The 0.1.3 release also introduced non-blocking MCP operations and an upgrade to Quarkus 3.33.2. What sets Wanaku apart is its combination of MCP standardization, Apache Camel's 300+ enterprise components, and Quarkus cloud-native performance. It is community-driven and positioned as the first open-source MCP router, providing a central access point for AI agents to safely interact with enterprise data while eliminating duplicated integration code. Targeted at developers needing secure, scalable integration of LLMs with enterprise data, Wanaku simplifies scaling AI agent interactions across many endpoints. It emphasizes frictionless integration for generative AI use cases, with recent enhancements to service templates and community resources including a new website and blog.
Behind the Verdict
Wanaku fills a specific niche: it's one of the few open-source routers purpose-built for the Model Context Protocol (MCP). If you're engineering a system where autonomous agents need to query databases, talk to Kafka, or hit enterprise APIs—and you want centralized access control and auditing—Wanaku is a solid bet. The recent addition of a SQL tool service template (June 2026) and GitHub tools makes it more immediately useful for developers. The 0.1.3 release also brought non-blocking MCP operations, which matters for latency-sensitive agent loops. Where Wanaku falls short: it's not a product for non-developers. There's no managed cloud tier, no paid support (unless you count community forums), and the Apache Camel + Quarkus stack can be intimidating if your team leans Python-heavy. For a pure no-code integration platform, you'd look elsewhere. Compared to proprietary routers like those from LangChain or Anthropic, Wanaku gives you full control and no licensing fees, but you shoulder the operational burden. That said, its pluggable architecture and growing set of service templates reduce the boilerplate significantly. In practice, we'd reach for Wanaku when we want an open-source way to enforce security and governance across many agent-to-system connections, especially when those systems span HTTP, Kafka, and FTP. It's early-stage but actively maintained—the new website and blog signal a team committed to documentation and community growth. Just budget time for the learning curve if your team isn't already familiar with Camel.
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Use Cases
- Route AI agent requests to enterprise databases via MCP SQL tools.
- Enforce access control and audit logs for LLM interactions with sensitive systems.
- Scale agentic integrations from a few endpoints to hundreds using Apache Camel.
- Quickly expose internal APIs, file systems, or message queues as MCP tools.
- Build reusable tool templates for common enterprise integrations.
Limitations
- As a young open-source project, documentation and community support are still growing.
- It requires familiarity with MCP and enterprise integration patterns.
- No commercial support plan is available yet.
Integrations
Resources & Guides
Official links
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