MCP File Operations Agent

@dynstat

About MCP File Operations Agent

A working example of your own agents from the scratch and using it with the mcp servers from scratch

Config

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

{
  "mcpServers": {
    "File Operations Agent": {
      "command": "python",
      "args": [
        "file_agent_server.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 MCP File Operations Agent?

MCP File Operations Agent is a simple Model Context Protocol (MCP) server that exposes file system operations as tools, enabling AI agents to read file contents, write to files, and list directory contents through a client-server architecture. It is built for developers integrating file manipulation into MCP-based workflows.

How to use MCP File Operations Agent?

Install the package with pip install -e ., then create a .env file with your API keys. Run the server with python file_agent_server.py and the client with python file_agent_client.py. The server supports both Stdio and SSE transports; see the provided code examples for tool definition and client connection.

Key features of MCP File Operations Agent

Read file contents and return them as text.
Write content to specified files.
List directory contents.
Supports Stdio and SSE transport layers.
Includes a client that integrates with Google's Gemini API.

Use cases of MCP File Operations Agent

Allow a Gemini-based agent to read configuration or log files.
Enable an MCP client to write generated content to disk.
Provide an AI assistant with the ability to browse project directories.
Integrate file operations into Cursor IDE via the .cursor/mcp.json configuration.

FAQ from MCP File Operations Agent

What dependencies are required?

Python 3.12 or higher, and the packages mcp[cli]>=1.6.0, google-genai>=1.12.1, and python-dotenv.

How do I configure API keys?

Create a .env file in the project root with your API keys, following the format shown in .env-sample.

What file operations are available?

The server provides three tools: read_file to read a file, write_file to write content to a file, and a tool to list directory contents (not explicitly named but implied by features).

How does transport work?

The server can run via Stdio (local inter-process communication) or SSE (HTTP-based, suitable for network interactions). Both are demonstrated with complete code examples in the README.

Can this be used with Cursor IDE?

Yes, configure the server in .cursor/mcp.json with the appropriate command and path to file_agent_server.py.

Frequently asked questions

What dependencies are required?

Python 3.12 or higher, and the packages `mcp[cli]>=1.6.0`, `google-genai>=1.12.1`, and `python-dotenv`.

How do I configure API keys?

Create a `.env` file in the project root with your API keys, following the format shown in `.env-sample`.

What file operations are available?

The server provides three tools: `read_file` to read a file, `write_file` to write content to a file, and a tool to list directory contents (not explicitly named but implied by features).

How does transport work?

The server can run via Stdio (local inter-process communication) or SSE (HTTP-based, suitable for network interactions). Both are demonstrated with complete code examples in the README.

Can this be used with Cursor IDE?

Yes, configure the server in `.cursor/mcp.json` with the appropriate command and path to `file_agent_server.py`.

Comments

Basic information

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