Example API Tool Setup

This project demonstrates two approaches for integrating external API tools with Pydantic AI agents.

Project Structure

l1-mcp/ (Level 1 - MCP Integration)

Uses Model Context Protocol (MCP) servers for tool integration. Tools are loaded from an external MCP server configured via .mcp.json.

Key Features:

• External tool server via MCP protocol
• Dynamic tool loading
• Configuration-driven approach

l2-tool/ (Level 2 - Direct Tool Integration)

Directly initializes and registers connector tools within the agent code.

Key Features:

• In-memory tool registration
• Direct connector initialization
• Programmatic approach

Setup

Prerequisites

• Python 3.12 or higher
• Environment variables configured (see below)

Installation

1. Clone or navigate to the project directory:

   cd /path/to/example-api-tool-setup

2. Run the setup script to create the shared virtual environment:

   ./setup.sh

   This will:

   • Create a shared venv/ directory at the project root
   • Install all required dependencies
   • Set up the environment for both l1-mcp and l2-tool

Environment Configuration

Both implementations share a single .env file at the project root. Copy the .env.example file as a starting point:

cp .env.example .env
# Edit .env and add your API keys

Required environment variables:

• ANTHROPIC_API_KEY - Claude API key
• GONG_ACCESS_KEY - Gong API access key
• GONG_ACCESS_KEY_SECRET - Gong API secret
• LANGSMITH_* - (Optional) LangSmith tracing configuration
• AIRBYTE_* - Airbyte configuration for l2-tool direct integration

Running the Applications

Both implementations use the same Gradio chat interface and can be run independently.

Run l1-mcp (MCP Integration)

cd l1-mcp
./run.sh

Run l2-tool (Direct Tools)

cd l2-tool
./run.sh

The Gradio interface will be available at: http://localhost:8000