Wanaku
Open-source governed action proxy that sits between AI agents and enterprise systems, enforcing policy, identity and audit before any agent touches a backend.
Wanaku is a credible open-source pick if you are building agentic applications that must act on enterprise systems under audit. Its distinguishing choice is that it is an action proxy, not a traffic passthrough: Camel routes do the work, and policy, identity, and audit live in the proxy. The 0.2.0 release (July 2026) adds a Kubernetes operator and production hardening, which makes it defensible for real deployments. If you are not on Java/Camel and want a managed MCP gateway with vendor SLAs, look elsewhere. For Python-centric teams, commercial managed gateways will likely be faster to adopt.
Verified 21h ago · liveness 66/100 · cite: rightaichoice.com/tools/wanaku
- Developers building agentic AI applications
- Teams needing governed, auditable LLM-to-enterprise integration
- Organizations with Java/Apache Camel expertise
- Production deployments needing Kubernetes orchestration
- Non-technical users who need a no-code integration platform
- Teams that require a commercial vendor with paid support and SLAs
- Projects needing a simple API passthrough without routing logic
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Skip Wanaku if your team is Python-centric, wants a managed gateway with SLAs, or needs a no-code integration platform — its value depends on running and extending Apache Camel routes yourself.
Wanaku is open source with no published paid tiers, so cost is your own infrastructure and engineering time. That makes it budget-friendly for solo developers and mid-size Java teams who can self-host, and comparatively expensive for small teams without Camel skills, who effectively pay in ramp-up time. Commercial managed MCP gateways charge subscriptions but bundle support and onboarding — that trade is the real pricing decision here.
In short
Wanaku — Open-source governed action proxy that sits between AI agents and enterprise systems, enforcing policy, identity and audit before any agent touches a backend. Best for Developers building agentic AI applications, Teams needing governed, auditable LLM-to-enterprise integration, Organizations with Java/Apache Camel expertise. Free to use.
What's new in Wanaku
Checked todayAcross the latest 4 updates: 1 launch, 1 changelog entry and 2 news mentions.
Wanaku 0.2.0 Released: Production Hardening and Enhanced Security
Wanaku 0.2.0 brings production hardening, enhanced security, a Kubernetes operator, and improved developer tooling, marking a major step toward enterprise readiness.
Building an MCP SQL Tool for LLMs with Wanaku and Apache Camel
Walkthrough of using Wanaku's SQL tool service template to connect LLMs to relational databases over MCP for real-time queries.
Wanaku 0.1.3 Released
Adds GitHub tools, service template improvements, non-blocking MCP operations, and upgrades to Quarkus 3.33.2.
Welcome to the New Wanaku Website
Launched a new website with a homepage, blog, community page, and reorganized documentation, including docs for the Rust-based Wanaku Next and the Java/Quarkus Wanaku Barn.
What people actually say about Wanaku — is it worth it?
We scanned public community sources for Wanaku on Aug 5, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Our own analysis of that scan says the posts were off-subject. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
Viability Score
How well maintained and how widely used is Wanaku? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Action proxy that executes tool calls through Apache Camel routes
- Intercepts tool calls, agent-to-agent messages, and inference traffic
- Policy enforcement in the proxy layer so agents cannot bypass it
- Identity and access control for agent actions
- Data controls and audit logging on backend operations
- 300+ Apache Camel components exposed as MCP tools
- MCP (Model Context Protocol) tool exposure for agents
- Service templates for reusable integrations
- SQL tool service template for database queries
- GitHub tools integration
- Non-blocking MCP operations
- Kubernetes operator for deployment
- CLI and web UI for setup and management
- Custom capabilities SDK in plain Java
- Scalability from a few to thousands of endpoints
About Wanaku
Wanaku is an open-source governed action proxy for AI agents. It sits between agents and the systems they act on, intercepting tool calls, agent-to-agent messages, and inference traffic. Integration developers build Apache Camel routes and publish them as tools; agents call those tools with parameters, but Wanaku executes the actual work. Because policy, identity, data controls, and audit run inside the proxy, agents never reach backend systems directly and cannot bypass governance. Built on Apache Camel and Quarkus, Wanaku exposes 300+ Camel components (HTTP, Kafka, FTP, SQL databases, GitHub) as MCP tools for agents. The 0.2.0 release (July 2026) adds production hardening, enhanced security, a Kubernetes operator, and improved developer tooling; 0.1.3 added GitHub tools, service template improvements, non-blocking MCP operations, and a Quarkus 3.33.2 upgrade. It is aimed at developers building agentic applications who need governed, auditable LLM-to-enterprise integration, and it is distributed as open source with no proprietary lock-in. The main friction is the MCP and Apache Camel learning curve, especially for teams outside the Java ecosystem.
Behind the Verdict
Wanaku's core bet is that the hard problem in agentic integration is not connecting an LLM to a database — it is governing what the agent is allowed to do once connected. That is why it positions itself as an action proxy rather than a gateway. The proxy runs the Camel route itself, so the agent supplies parameters and never holds credentials or touches the backend. Policy, identity, data controls, and audit are all enforced at that layer. For teams that already run Apache Camel, the payoff is large: 300+ existing components become MCP tools without rewriting connectors. The service template system, including the SQL tool template demonstrated in the June 2026 blog post, shows how reusable integrations get packaged. Release 0.1.3 added non-blocking MCP operations and GitHub tools; 0.2.0 added a Kubernetes operator and production hardening. The honest weaknesses: the learning curve spans both MCP and Camel; documentation and community are still maturing; there is no published commercial support plan; and the next major version is Rust-based, so Java teams should watch that transition. It is not a no-code tool, and it does not include models. Choose Wanaku when you need self-hosted, auditable agent action routing and you have Java/Camel depth. Choose a commercial managed gateway if you need SLAs and faster onboarding.
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Real-world workflow fit
Concrete scenarios for the personas Wanaku actually fits — and what changes day-one when you adopt it.
Publishes an existing Apache Camel route as an MCP tool and points an agent at it, so the agent can query a relational database without holding credentials.
Outcome: The agent runs governed queries; policy, identity, and audit are enforced in the proxy, and the backend database is never exposed directly.
Deploys Wanaku with the Kubernetes operator from 0.2.0 and scales from a handful of tools to hundreds without redesigning the integration layer.
Outcome: A durable proxy layer that governs agent tool calls, agent-to-agent messages, and inference traffic across the organization.
Packages Kafka and HTTP operations as reusable service templates and exposes them as MCP tools so several agent teams share one governed connector set.
Outcome: New agents onboard faster because connectors are defined once and reused, with audit logging on every call.
Use Cases
- Route AI agent tool calls to enterprise databases and APIs under enforced policy
- Audit and control agent actions on sensitive systems from the proxy layer
- Expose 300+ Apache Camel integrations as MCP tools for agents
- Scale agent integration endpoints from a few to thousands using the Kubernetes operator
- Build reusable service templates for common enterprise integrations
- Give LLMs governed access to relational databases via the SQL tool template
- Intercept and govern agent-to-agent delegations and inference traffic
- Package custom Java capabilities via the Wanaku Capabilities SDK
Limitations
- Wanaku is an open-source proxy, not a model provider — it does not include any AI models.
- Adopting it means learning MCP, Apache Camel, and enterprise integration patterns, which is a real ramp for teams outside Java.
- Documentation and community support are still maturing, and no commercial support plan is mentioned.
- There is no built-in UI for non-technical users; management is via CLI and a web UI aimed at developers.
- The next major version is Rust-based, which means Java/Quarkus shops should track that transition before committing deep customization.
- The project is young — 0.2.0 shipped July 2026.
as of 2026-09-14
Verification history
We have re-verified Wanaku 7 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 7 verification passes.
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where Wanaku's pricing actually pencils out — and where peers do it cheaper.
Wanaku is open source with no published paid tiers, so cost is your own infrastructure and engineering time. That makes it budget-friendly for solo developers and mid-size Java teams who can self-host, and comparatively expensive for small teams without Camel skills, who effectively pay in ramp-up time. Commercial managed MCP gateways charge subscriptions but bundle support and onboarding — that trade is the real pricing decision here.
Setup time & first value
How long it actually takes to get something useful out of Wanaku — broken out by persona, not the marketing-page minute.
For developers already fluent in Java, Quarkus, and Apache Camel and with MCP concepts, first value is typically same-day: publish a Camel route as a tool and call it. For Java teams new to MCP, expect a few days of reading and a first working tool the same week. Python-centric teams without Java experience should plan weeks, not days, and should evaluate managed alternatives first.
Switching to or from Wanaku
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From direct LLM-to-database connectors: replace direct credentials with a Wanaku SQL tool service template so queries are governed and audited
- →From a plain API gateway: move routing logic into Apache Camel routes and expose them as MCP tools so agents cannot bypass policy
- →From custom glue code calling enterprise systems: port each connector into a Camel route published as a Wanaku tool
- ↗To a commercial managed MCP gateway: re-point agent tool definitions at the vendor's endpoint; expect to reimplement Camel routing logic in the vendor's model
- ↗To a framework-native tool layer: export tool schemas from Wanaku and rebuild the execution layer inside your agent framework
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Wanaku”, and we withheld 6: 6 could not be judged, because “Wanaku” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Wanaku.
Official links
Tools that pair well with Wanaku
Common stack mates teams adopt alongside Wanaku, with the specific reason each pairing earns its keep.
Featured Head-to-Head Comparisons
Wanaku vs Temporal Ai
Choose Temporal AI if you need bulletproof durability for AI agents and long-running workflows, with rich SDKs and human-in-the-loop. Choose Wanaku if your priority is securely routing MCP calls from LLMs to enterprise systems (databases, protocols) with access control and auditing. They solve different problems: Temporal orchestrates execution reliability, Wanaku bridges AI agents to backends.
Wanaku vs Spider Cloud
Spider Cloud and Wanaku serve fundamentally different purposes. Spider Cloud is a high-performance web scraping API for feeding real-time data into AI agents, while Wanaku is an MCP router for connecting AI agents to enterprise systems. Choose Spider Cloud if you need fast, cheap web data extraction; choose Wanaku if you need to securely integrate LLMs with internal tools and databases.
Wanaku vs Presto Voice
Presto Voice and Wanaku solve completely different problems. If you run a multi-location QSR wanting to automate drive-thru orders and boost revenue via voice AI upselling, Presto Voice is the purpose-built choice though it requires a sales call for pricing. If you're a developer or team building autonomous AI agents that need secure, scalable integration with enterprise systems via MCP, the free open-source Wanaku router is a no-brainer.
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