Inori FAQs

Question 1

What are the main features of Inori?

Accepted Answer

Inori includes Go and Python implementations of an MCP server, an example book search tool, easy integration with external APIs, a client for interacting with the server, and debugging tools.

Question 2

What is Inori?

Accepted Answer

Inori is a tool that provides a simple MCP (Model Context Protocol) server implementation, allowing you to easily interact with large language models.

Question 3

How can I use Inori to test tool calls with LLMs?

Accepted Answer

Inori provides debugging tools and an example book search tool. You can use the inspector (npx -y @modelcontextprotocol/inspector) to test calls and see if the LLM correctly identifies and uses the specified tools. Modify the python client script with your LLM base URL and use QWQ-32B or similar models to trigger tool calls.

Question 4

What dependencies does Inori have?

Accepted Answer

Inori requires Go or Python (depending on the server implementation you choose) and a compatible LLM with tool calling capabilities. The client also depends on an OpenAI compatible API base URL and uses .env.

Question 5

What is MCP?

Accepted Answer

MCP stands for Model Context Protocol. It's a protocol that enables communication and interaction between large language models and external tools or services.

Inori

Key Features

Use Cases

Inori

Key Features

Use Cases