2_adk_mcp

ADK MCP

This directory contains implementations demonstrating Model Context Protocol (MCP) integration with ADK agents.

Table of Contents

• Overview
• Project Structure
• Implementations
  • GitHub MCP Agent
  • Firecrawl MCP Agent
• Getting Started
  • Prerequisites
  • Installation
  • Usage
• References

Overview

MCP (Model Context Protocol) allows agents to connect to external services and tools through a standardized protocol. This enables agents to access a wide variety of third-party services and APIs.

MCP Tools provide a standardized way to connect ADK agents to external services like GitHub, Firecrawl, and other third-party APIs through the Model Context Protocol.

Project Structure

2_adk_mcp/
├── adk_mcp_github_agent/
│   ├── agent.py         # Agent definition with GitHub MCP toolset
│   ├── __init__.py      # Package initialization
│   └── .env.example     # Example environment variables template
├── adk_mcp_firecrawl_agent/
│   ├── agent.py         # Agent definition with Firecrawl MCP client
│   ├── __init__.py      # Package initialization
│   └── .env.example     # Example environment variables template
├── requirements.txt     # Python dependencies
└── README.md            # This file

Implementations

GitHub MCP Agent

Demonstrates connecting to GitHub via MCP toolset using the GitHub Copilot MCP API.

Key Features:

• MCP toolset integration
• GitHub API access
• Read-only operations
• Bearer token authentication

Directory: adk_mcp_github_agent/

See: adk_mcp_github_agent/README.md

Firecrawl MCP Agent

Demonstrates using Firecrawl MCP client for web scraping and crawling capabilities.

Key Features:

• Firecrawl MCP integration
• Web scraping capabilities
• Content extraction
• Stdio connection via npx

Directory: adk_mcp_firecrawl_agent/

See: adk_mcp_firecrawl_agent/README.md

Getting Started

Prerequisites

• Python 3.11 or later
• uv or pip package manager
• Google API key from Google AI Studio
• Service-specific tokens (e.g., GitHub token, Firecrawl API key)

Installation

Install dependencies using uv (recommended) or pip:

Using uv:

# Install uv if not already installed
curl -LsSf https://astral.sh/uv/install.sh | sh

# Create virtual environment (if needed)
uv venv

# Install dependencies
uv pip install -r requirements.txt

Using pip:

# Create and activate virtual environment (recommended)
python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Usage

1. Navigate to any implementation directory
2. Follow the README.md in that directory
3. Set up your .env file with required API keys and tokens
4. Run from this directory (2_adk_mcp) with:
   • adk run <agent-name> for CLI
   • adk web for web interface (then select the agent in the browser)

References

• ADK MCP Tools Documentation
• MCP Protocol
• Third-party Tools