MCP Flow

MCP Flow

A Python-based chat workflow engine that integrates FastAPI, CLI, and Google ADK for unified AI Q&A processes and extended functionality

Artificial intelligence chatbots Developer tools #Workflow Engine #AI Integration #FastAPI #ADK Tool .Python

rating : 2 points

downloads : 8.6K

update time : 2025-04-28

What is MCP Flow?

MCP Flow is an intelligent chat workflow engine that helps you centrally manage different AI Q&A processes. By integrating multiple AI agents, formatting tools, and external APIs, it can automatically handle complex conversation scenarios.

How to use MCP Flow?

You can use MCP Flow through the REST API or command-line tools. First, install the system, then configure the workflow according to your needs, and finally send requests via the API or CLI.

Use Cases

Suitable for enterprises that need to integrate multiple AI services, teams developing intelligent customer service systems, or individual developers who want to automate complex conversation processes.

Main Features

Multi-workflow Support

Supports multiple workflow types such as formatting, answering, and ADK agents

REST API Interface

Provides standardized REST interfaces through FastAPI for easy integration

Command-line Tool

Provides a CLI tool for quick testing and debugging of workflows

Google ADK Integration

Seamlessly integrates Google Agent Development Kit, supporting custom agents and tools

Extensible Architecture

Modular design for easy addition of new workflows and plugin tools

Advantages

Centrally manage multiple AI services and workflows

Flexible extensibility to add new features as needed

Provide both API and CLI usage methods

Integrate advanced Google AI technology

Limitations

Requires a certain technical foundation for configuration

ADK integration requires a Google developer account

Initial setup may take time to get familiar with

How to Use

Install the System

Clone the code repository and install dependencies

Start the Service

Run the FastAPI server

Configure the Workflow

Edit the configuration file to set the required workflow

Test and Use

Test your workflow through the API or CLI

Usage Examples

Intelligent Customer Service System

Integrate multiple AI services to provide a unified customer service interface

Multi-AI Agent Collaboration

Automatically select the most suitable AI agent to answer based on different question types

Data Formatting

Automatically format AI answers into a specified structure

Frequently Asked Questions

What technical foundation is required to use MCP Flow?

Which AI services are supported for integration?

Is there a visual interface?

How to add a custom workflow?

Related Resources

Google ADK Official Documentation

Official code repository and documentation for Google Agent Development Kit

FastAPI Documentation

Official documentation for the FastAPI framework

Python Official Tutorial

Official tutorial for the Python programming language

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