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Savi-04

Local File Reader MCP Server

by Savi-04

Local File Reader MCP Server

This is a Model Context Protocol (MCP) server that provides an analyze_spending tool to AI assistants. It securely reads local files (CSV, JSON, TXT, MD, PDF, etc.) from the project directory and returns their text contents to the AI for analysis.

Features

  • Supports multiple formats: Reads text-based files out of the box, and uses pdf-parse to extract text from PDFs.

  • Secure:

    • Prevents path traversal and symlink attacks (only reads files inside the project directory).

    • Prevents Out of Memory (OOM) crashes by enforcing a 10MB file size limit.

    • Sanitizes error messages to prevent sensitive path leakage.

Related MCP server: Filesystem MCP

Prerequisites

  • Node.js (v18 or higher recommended)

  • npm

Setup & Installation

  1. Open your terminal in the project directory (mcp-project).

  2. Install the dependencies:

    npm install

Testing the Server (Using the MCP Inspector)

The easiest way to test this server is to use the official MCP Inspector. This spins up a local web interface where you can pretend to be the AI and test the tool manually.

  1. Run the inspector command:

    npx @modelcontextprotocol/inspector node index.js
  2. The terminal will output a URL like http://localhost:6274/?MCP_PROXY_AUTH_TOKEN=.... Open this link in your browser.

  3. In the Inspector UI, go to the Tools tab.

  4. Select analyze_spending.

  5. Enter the filename of a file that exists in this directory (e.g. test.csv or document.pdf) and hit Run. The contents of the file will be returned!

Using the Server with a real AI Agent

You can hook this local server up to any MCP-compatible AI client (like Claude Desktop or Cursor).

For example, to configure it in Claude Desktop, you would add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "local-file-reader": {
      "command": "node",
      "args": [
        "/absolute/path/to/your/mcp-project/index.js"
      ]
    }
  }
}

Once connected, you can ask the AI: "Can you analyze my spending in the data.csv file?" and it will seamlessly use this tool to fetch the file contents.

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