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MCP Flow - Chat Workflow Engine with ADK Integration

@alelcold

Repository

Basic information

Category

AI & Agents

Transports

stdio

Author

alelcold

About MCP Flow - Chat Workflow Engine with ADK Integration

Try to Set MCP Server

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

MCP Flow - Chat Workflow Engine with ADK Integration config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

MCP Flow - Chat Workflow Engine with ADK Integration tools

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Overview

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

Frequently asked questions

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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