Wanaku

The Wanaku MCP router is an AI application router based on the Model Context Protocol (MCP), aiming to standardize the way applications provide context to large language models (LLMs).

Artificial intelligence chatbots Developer tools #AI router #Protocol standardization #Context management .Java

rating : 2.5 points

downloads : 8.4K

update time : 2025-04-29

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What is Wanaku?

Wanaku is an intelligent router based on the MCP protocol, providing a standardized context transfer mechanism for AI applications. It acts as a bridge connecting various applications with large language models (LLMs) to ensure the standardized transmission of context information.

How to use Wanaku?

You can connect your application to the MCP network through simple configuration. For detailed steps, please refer to the user guide. The core process includes: Install the routing service → Configure the application endpoint → Define the context template → Start the connection.

Use cases

It is suitable for scenarios where business systems need to be integrated with LLMs, such as AI applications that require maintaining conversation context, like intelligent customer service systems, automated document processing, and knowledge base Q&A.

Main features

Protocol standardization

Unify the interaction methods between different applications and LLMs through the MCP protocol, eliminating the complexity of docking.

Context management

Automatically maintain the context relationship of multi - round conversations and support custom context retention strategies.

Multi - backend support

It can connect to multiple LLM service providers simultaneously to achieve load balancing and failover.

Advantages

Standardized interfaces reduce integration costs

Open - source protocols avoid vendor lock - in

Lightweight design is suitable for edge deployment

Limitations

The application side needs to adapt to the MCP protocol

There may be delays in scenarios with high real - time requirements

Currently, only text - based context is supported

How to use

Install the service

Install the routing service through Docker or local compilation.

Configure the application endpoint

Define the context template

Create a context structure template specific to the application.

Usage examples

E - commerce customer service system integration

Connect the order system with the LLM customer service and automatically transfer the user's historical orders as context.

Medical knowledge base Q&A

Connect the electronic medical record system with the medical knowledge base and automatically associate the patient's medical history during the consultation.