What is Python Pydantic Ai Mcp Agent

python-pydantic-ai-mcp-agent is an AI agent implementation that utilizes Pydantic and Chainlit to facilitate seamless integration of multiple tools through MCP (Multi-Command Protocol).

Use cases

Use cases include automated web browsing for data extraction, building interactive chatbots, integrating local language models for enhanced AI capabilities, and developing applications that require seamless communication between different software tools.

How to use

To use python-pydantic-ai-mcp-agent, clone the repository, install the required Python and Node.js dependencies, configure the MCP settings in the provided JSON template, and run the Chainlit interface or the agent directly using the specified commands.

Key features

Key features include web browsing capabilities with automated interactions, integration with Ollama for local LLM support, an interactive chat interface based on Chainlit, type-safe data handling using Pydantic models, and configurable MCP server integration.

Where to use

python-pydantic-ai-mcp-agent can be used in various fields such as AI development, web automation, data processing, and any application requiring interaction with multiple tools through a unified interface.

Pydantic MCP Agent with Chainlit

A powerful AI agent implementation using Pydantic and Chainlit, capable of web browsing and interaction through MCP (Multi-Command Protocol).

Features

• Web browsing capabilities with automated interactions
• Integration with Ollama for local LLM support
• Chainlit-based interactive chat interface
• Pydantic models for type-safe data handling
• Configurable MCP server integration

Prerequisites

• Python 3.8+
• Node.js and npm (for MCP server)
• Ollama installed locally
• MCP server access

Installation

1. Clone the repository:

git clone https://github.com/RyanNg1403/pydantic-ai-mcp-agent-with-chainlit.git
cd pydantic-ai-mcp-agent-with-chainlit

2. Install Python dependencies:

pip install -r requirements.txt

3. Install Node.js dependencies:

npm install

Configuration

1. Copy the template configuration file:

cp mcp_config.template.json mcp_config.json

2. Edit mcp_config.json with your configuration settings. The file is ignored by git for security.

Usage

Running the Chainlit Interface

chainlit run pydantic_mcp_chainlit.py

Running the Agent Directly

python pydantic_mcp_agent.py

Project Structure

• pydantic_mcp_agent.py: Core agent implementation
• pydantic_mcp_chainlit.py: Chainlit interface implementation
• mcp_client.py: MCP client implementation
• requirements.txt: Python dependencies
• mcp_config.template.json: Template for configuration
• .gitignore: Specifies which files git should ignore

Environment Variables

The following environment variables can be set in your .env file:

• EXA_API_KEY: Your MCP API key
• OLLAMA_HOST: Ollama host address (default: http://localhost:11434)

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request