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MCP Flow - Chat Workflow Engine with ADK Integration

@alelcold

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

alelcold

关于 MCP Flow - Chat Workflow Engine with ADK Integration

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#mcp-flow#chat-workflow#adk-integration

MCP Flow - Chat Workflow Engine with ADK Integration 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

MCP Flow - Chat Workflow Engine with ADK Integration 工具

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工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is 🧠 MCP Flow - Chat Workflow Engine with ADK Integration?

It is a clean, extensible chat workflow engine built with Python, FastAPI, CLI, and Google’s Agent Development Kit (ADK). Designed to unify AI question‑answering flows, it integrates multiple AI agents, formatting tools, and external APIs.

How to use 🧠 MCP Flow - Chat Workflow Engine with ADK Integration?

Clone the repository, navigate to mcp-flow, and run pip install -r requirements.txt. Afterwards, the server can be used via its FastAPI REST API or the included CLI tool to execute and test workflows.

Key features of 🧠 MCP Flow - Chat Workflow Engine with ADK Integration

  • Supports multiple workflow types: formatting, answering, ADK agent
  • Provides a FastAPI REST API endpoint
  • Includes a CLI tool for quick testing
  • Integrates Google ADK for custom agents and tools
  • Extensible workflow and plug‑in tool architecture

Use cases of 🧠 MCP Flow - Chat Workflow Engine with ADK Integration

  • Build unified AI question‑answering pipelines
  • Combine multiple AI agents in a single workflow
  • Integrate formatting tools and external APIs into chat flows
  • Test workflow logic rapidly via the command line

常见问题

1

What runtime does the server require?

It runs on Python and requires `pip install -r requirements.txt` to set up dependencies.

2

Which AI framework does it integrate?

It integrates Google’s Agent Development Kit (adk‑python) for building custom agents and tools.

3

How can I interact with the server?

Interaction is possible through a FastAPI REST API and a dedicated command‑line interface (CLI).

4

What transport protocols are supported?

The server provides REST (HTTP) via FastAPI and a local CLI transport for direct testing.

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