MCP Filesystem Server

Go MCP server enabling seamless integration of LLM applications with external data sources and tools.

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6

GitHub Stars

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Language

6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "qiangmzsx-mcp-filesystem-server": {
      "command": "mcp-filesystem-server",
      "args": [
        "/Users/username/Desktop",
        "/path/to/other/allowed/dir"
      ]
    }
  }
}

You get an MCP server implemented in Go that lets your language models access external data sources and tools through a flexible, standard interface. It acts as a bridge between your LLM workflows and filesystem data, so you can query and retrieve information from your own directories and files as part of your AI-powered tasks.

How to use

You run the filesystem MCP server locally and point your MCP client to it. The server exposes access to directories you designate, enabling your LLM workflows to read from those locations and filter results as part of data retrieval and reasoning tasks. To use it, install the server, start it, and configure your MCP client to connect to the local process. Then you can query files, directories, or metadata through the MCP protocol, and your client can compose responses using the filesystem data as sources.

How to install

Prerequisites: you need Go installed on your machine to build and install the server.

go install github.com/qiangmzsx/mcp-filesystem-server

After installation, run the server with the directories you want to expose. Use your actual paths in place of the placeholders shown below.

{
  "mcpServers": {
    "filesystem": {
      "command": "mcp-filesystem-server",
      "args": [
        "/Users/username/Desktop",
        "/path/to/other/allowed/dir"
      ]
    }
  }
}

Additional sections

Configuration notes: The server is configured by providing a command that starts the filesystem MCP server along with any allowed directories you want to expose. You can declare multiple directories in the args array to broaden the accessible data scope. Security considerations include limiting the exposed paths to directories you control and trust, as the MCP client will be able to access contents from those locations during inference.

Notes on usage: Use the filesystem MCP server to enrich responses with local data, perform searches, or verify facts against your own data sources. You can combine filesystem data with other MCP-backed sources to create robust, data-aware AI workflows.

License: This MCP server is available under the MIT License, allowing free use, modification, and distribution in your own projects, subject to the terms of the license.