Project Overview

Project Overview

By WillChangeThisLater GitHub

Use MCP servers with OpenAI Agents

easy-mcp openai-agents
Overview

What is Easy-MCP?

Easy-MCP is a project that integrates MCP servers with OpenAI agents, allowing users to leverage AI capabilities for various tasks.

How to use Easy-MCP?

To use Easy-MCP, set up the environment by running the setup.sh script, install the necessary dependencies, and execute the agent.py script with the desired server configurations.

Key features of Easy-MCP?

  • Integration of multiple MCP servers with OpenAI agents.
  • Ability to configure server access for optimized performance.
  • Debug mode for testing server setups without executing the agent.

Use cases of Easy-MCP?

  1. Automating web searches using the Lynx server.
  2. Managing files and directories through the file system server.
  3. Conducting research and gathering information efficiently.

FAQ from Easy-MCP?

  • What is an MCP server?

MCP servers are modular components that can be configured to perform specific tasks, such as web searching or file management.

  • How do I configure the servers?

Servers are configured in the servers.yaml file, where you can specify the server name, description, command, and environment variables.

  • Is there a way to test the setup before running the agent?

Yes! You can use the --debug flag to initialize servers without executing the agent.

Content

Project Overview

MCP servers + OpenAI agents.

Setting up the Environment

  1. Create and Activate a Virtual Environment:

    • Run the provided setup.sh script to establish a virtual environment using Python 3.13. 
      ./setup.sh
    • The script creates a virtual environment and installs all required Python packages from requirements.txt.

  2. Install Project Dependencies:

    • Ensure you have the necessary external tools and services for the MCP servers you intend to run:
      • Lynx: Required for the lynx server, which interfaces with the Lynx terminal web search tool.
      • Docker: Required for the puppeteer and github servers, enabling Chrome control and GitHub interactions, respectively.
      • Node.js: Required for the fs server, using the npx command.

Usage Guide

Running agent.py

Basic Execution

  • You can run the agent using all the servers you have configured in servers.yaml like this

    python agent.py

  • You can choose which servers the agent will have access to with:

    # gives agent access to file system (for local file browsing) and lynx (for websearch)
python agent.py --servers fs lynx

    In my experience this results in better performance since the agent is less likely to pick the wrong tool

  • Debug Mode:

    • Use the --debug flag to initialize servers without executing the agent. This is useful if you want to make sure the servers are set up correctly 
      python agent.py --debug

Configuration

The servers are configured in servers.yaml, where each server entry includes:

  • Name: Identifier for the server.
  • Description: Brief description of the server's functionality.
  • Command & Arguments: Command-line instructions to start the server.
  • Environment Variables: Any additional environment configurations needed.

You'll typically find these in github repos for MCP servers

Roll your own

You can roll your own MCP server in the mcp-servers directory

What do I use this for?

If I am trying to figure out how to do something (like setting up QEMU) I will often use agent.py to do the initial research for me

"find links relevant to QEMU setup on ubuntu" | python agent.py --servers lynx
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