Project Overview

@WillChangeThisLater

About Project Overview

Use MCP servers with OpenAI Agents

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "easy-mcp": {
      "command": "python",
      "args": [
        "agent.py"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Project Overview?

Project Overview combines MCP (Model Context Protocol) servers with OpenAI agents, enabling automated research and file system tasks. It is intended for developers who want to run configurable, multi-server AI agents from the command line.

How to use Project Overview?

Set up the environment with the provided setup.sh script (Python 3.13 virtual environment + dependencies), install required external tools (Lynx for web search, Docker for puppeteer/GitHub, Node.js for file system server), configure servers in servers.yaml, then run python agent.py with optional --servers flags (e.g., python agent.py --servers fs lynx) or --debug for testing setup.

Key features of Project Overview

Integrates multiple MCP servers (fs, lynx, puppeteer, github)
Command-line agent with configurable server selection
Debug mode to verify server configuration
Supports custom MCP servers in mcp-servers directory
Environment setup via automated shell script
Server configuration via YAML file

Use cases of Project Overview

Automated web research: pipe a research prompt into the lynx server
Local file system browsing with the fs server
GitHub repository interactions via the github server
Chrome control through the puppeteer server
Multi-server workflows where an agent selects appropriate tools

FAQ from Project Overview

What external dependencies are required?

Lynx (for the lynx server), Docker (for puppeteer and github servers), and Node.js (for the fs server).

How do I configure which servers the agent can use?

Edit servers.yaml with the server's name, description, command/arguments, and environment variables. Then select servers at runtime with the --servers flag.

Can I run only specific servers?

Yes, use python agent.py --servers <server1> <server2>. This can improve performance by reducing the chance the agent picks the wrong tool.

How do I test if servers are set up correctly?

Use the --debug flag to initialize servers without executing the agent: python agent.py --debug.

Can I create my own MCP server?

Yes, you can add custom servers in the mcp-servers directory.

Frequently asked questions

What external dependencies are required?

Lynx (for the lynx server), Docker (for puppeteer and github servers), and Node.js (for the fs server).

How do I configure which servers the agent can use?

Edit `servers.yaml` with the server's name, description, command/arguments, and environment variables. Then select servers at runtime with the `--servers` flag.

Can I run only specific servers?

Yes, use `python agent.py --servers <server1> <server2>`. This can improve performance by reducing the chance the agent picks the wrong tool.

How do I test if servers are set up correctly?

Use the `--debug` flag to initialize servers without executing the agent: `python agent.py --debug`.

Can I create my own MCP server?

Yes, you can add custom servers in the `mcp-servers` directory.

Comments

Basic information

More Other MCP servers

Mcp

browsermcp

Browser MCP is a Model Context Provider (MCP) server that allows AI applications to control your browser

6.8K

🪟 Windows-MCP

CursorTouch

MCP Server for Computer Use in Windows

6.3K

DeepMark

DeepMark helps teachers deliver rapid, consistent marking with meaningful feedback for every student — in a fraction of the time. What once took a week, now takes one free period.

YOUB

Connect your AI assistant to your own YOUB endurance training account. Read recorded activities with full analysis, planned sessions, race goals, wellness (HRV, sleep, resting HR) and your athletic profile. Create or mov

Unity MCP ✨

justinpbarnett

Unity MCP acts as a bridge between AI assistants and your Unity Editor. Give your LLM tools to manage assets, control scenes, edit scripts, and automate tasks within Unity.

12.2K