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MCP Flow
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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 chatbotsDeveloper tools#Workflow Engine#AI Integration#FastAPI#ADK Tool.Python
2 points
10.2K
Open Site

Overview

Content Details

Alternatives

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

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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