What is Smolagents Mcps

SmolAgents-MCPs is an AI assistant built using the SmolAgents library, designed to perform web searches and scrape websites by integrating with Brave Search and Crawl4ai Model Context Protocols (MCP) servers.

Use cases

Use cases include automating web searches for research, scraping data from websites for analysis, and integrating with other tools to enhance web interaction capabilities.

How to use

To use SmolAgents-MCPs, clone the repository, install the required dependencies, set up your environment variables with your API keys, and run the script ‘smolagent_with_mcp.py’. Interact with the assistant by typing your search queries.

Key features

Key features include modular design for easy addition of new MCP servers and tools, structured output for tool calls, and an object-oriented approach for better extensibility.

Where to use

SmolAgents-MCPs can be used in various fields such as web development, data scraping, research, and any application requiring automated web searches and data extraction.

SmolAgents + MCP servers

This project demonstrates building an AI assistant using the SmolAgents library that can perform web searches and scrape/crawl websites by integrating with the Brave Search and the Crawl4ai Model Context Protocols (MCP) servers.

Requirements

Before running this project, ensure you have the following dependencies installed:

• smolagents
• python-dotenv
• mcp
• @modelcontextprotocol/server-brave-search (installed globally via npm/npx)
• litellm

You can install the Python packages using pip:

pip install -r requirements.txt

Ensure you have Node.js and npm/npx and uv installed to run the MCP servers.

Environment Variables

Create a .env file in the root directory of the project and add the following variables:

BRAVE_API_KEY=your_brave_api_key
OPENAI_API_KEY=your_openai_api_key

Replace your_brave_api_key and your_openai_api_key with your actual API keys.

Usage

1. Clone the repository or download the script (smolagent_with_mcp.py).

2. Navigate to the project directory in your terminal.

3. Run the script:

   python smolagent_with_mcp.py
   

4. Interact with the assistant by typing your search queries. Type exit or quit to terminate the session.

the code encapsulates the agent initialization and the main interaction loop within a Python class (SmolAgentWithMCP). This object-oriented approach offers modularity and makes it easier to extend the agent’s capabilities, such as integrating additional MCP servers and their tools.

Notes

• Ensure that npx is installed and available in your system’s PATH, as it is required to run the Brave Search MCP server.
• The ToolCallingAgent in SmolAgents is designed to output tool calls in a structured format (like JSON) which are then executed by the environment (in this case, the script’s main loop using the MCPClient).

Adding More MCP Servers

The smolagent_with_mcp.py file is structured to allow for easily adding more MCP servers and their tools in a modular way. To add a new MCP server:

1. Define the StdioServerParameters for the new server. This involves specifying the command to run the server, its arguments, and any necessary environment variables (similar to how brave_server_params and crawl4ai_server_params are defined).

2. Add the newly defined server parameters object to the server_list in the main function. The BraveSearchAgentApp class will automatically initialize the new server and include its tools in the agent’s capabilities.

Example:

# Define parameters for a new server (replace with actual command and args)
new_server_params = StdioServerParameters(
    command="your_server_command",
    args=["arg1", "arg2"],
    env={"YOUR_API_KEY": os.getenv("YOUR_API_KEY")},
)

def main():
    # Define the list of MCP server parameters
    server_list = [
        brave_server_params,
        crawl4ai_server_params,
        new_server_params # Add the new server parameters here
        # Add other server parameters here as needed
    ]
    app = BraveSearchAgentApp(server_list)
    app.run()

if __name__ == "__main__":
    main()

MCP used in the project:

https://playbooks.com/mcp/ritvij14-crawl4ai
https://github.com/modelcontextprotocol/servers/tree/main/src/brave-search

License

This project is licensed under the MIT License. See the LICENSE file for more details.