Currently, everyone is talking about AI workflows, and there are several tools available to help us orchestrate AI workflows, such as Dify, langGraph, and n8n. However, those who have used these orchestration tools may have experienced that not only do they have a significant learning curve, but the flexibility of the orchestrated workflows is also limited.

In real life, many of the tasks we perform daily are not pre-scripted. Highly repetitive processes are indeed suitable for orchestration, but for variable and non-repetitive processes, these fixed-pattern workflows clearly lack flexibility. Orchestrating everything according to fixed patterns can be quite challenging when dealing with complex and ever-changing real-life scenarios.

To address this issue, ConsoleX AI has introduced a more innovative approach called "Agentic tool invocation", based on the tool use mechanisms of large language models. This allows users to create a series of "Unit Tools", each designed to perform the most basic tasks. Essentially, this equips the AI with a toolbox and a user manual for each tool, enabling the AI to autonomously combine these tools in various ways to achieve the final task goal.

This dynamic workflow offers greater flexibility and adaptability compared to pre-orchestrated workflows.

ConsoleX AI is the first tool that supports agentic tool invocation. Which means you can use ConsoleX AI to invoke a series of "Unit Tools" agentically, either in parallel or in sequence, to achieve the final task goal.

Here is a demonstration of an agentic shopping assistant using MCP server and computer use:

The initial prompt is:

Browse Amazon for 3 photography gifts for Dad's birthday, under $300. Save top picks to Obsidian.

Then the LLM will use computer use tool to browse Amazon, and save the top picks to Obsidian using Obsidian MCP tool. There are more than 10 intermediate steps in this process, but the LLM will autonomously invoke the tools to achieve the final goal, and actually complete the task pretty well.

There are too many AI chatbots in the market, what sets ConsoleX AI apart is its robust tool use system.

ConsoleX AI supports the following tool use related features:

Pre-built Tools: Access built-in tools for common tasks like web searching, image generation, and file parsing
Custom Tool Creation: Add your own tools with a simple JSON schema
Parallel & Sequential Tool Calling: Run multiple tools simultaneously or in sequence
Third-party Workflow Integration: Seamlessly connect with n8n, make dot com, and Dify workflows
MCP Server Integration: Support both SSE and STDIO types
Computer Use: Built-in compute capabilities for complex tasks
Tool Debugging: Test your tools with mock data

All of above features make ConsoleX AI the most comprehensive AI playground with agentic tool-using capabilities and ideal for developers to build your own AI agents. Don't hesitate to give ConsoleX AI a try, and let us know what you think!

— The ConsoleX Team