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MCP Flow - Chat Workflow Engine with ADK Integration

@alelcold

リポジトリ

基本情報

カテゴリ

AI とエージェント

トランスポート

stdio

作者

alelcold

MCP Flow - Chat Workflow Engine with ADK Integration について

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

MCP Flow - Chat Workflow Engine with ADK Integration の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

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MCP Flow - Chat Workflow Engine with ADK Integration のツール

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ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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

よくある質問

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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