📄 File Summarizer MCP Server

A custom MCP (Model Context Protocol) server that reads and summarizes the contents of any file type (PDF, DOCX, TXT, HTML, JSON, etc.) using Apache Tika, with optional multilingual support.

🧠 Easily plug this into Claude Desktop or other LLM tools to enable file-based context and summarization.

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🚀 Features

• 🔍 Reads content from any file type supported by Apache Tika
• ✨ Summarizes file content or raw input text
• 🌍 Auto-detects file language and translates non-English text before summarizing
• 🌐 Optional MCP tools to detect language and translate text
• 🧩 Async MCP tools for smooth integration
• 🛠️ Built with Python 3.12 and the FastMCP framework
• ✅ Ready for use with Claude Desktop or any other MCP client
• 📦 Published to PyPI for easy installation

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📦 Installation

From PyPI

pip install file-summarizer-mcp-server

From GitHub

git clone https://github.com/Muskan244/File_Summarizer_MCP_Server.git
cd File_Summarizer_MCP_Server
uv venv
source .venv/bin/activate  # or .venv\Scripts\activate on Windows
uv pip install -r requirements.txt

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🛠 Claude Desktop Integration

To use this server inside Claude Desktop:

1. Open (or create) your Claude config:

macOS

code ~/Library/Application\ Support/Claude/claude_desktop_config.json

Windows

code $env:AppData\Claude\claude_desktop_config.json

2. Add your server entry:

{
  "mcpServers": {
    "file-summarizer": {
      "command": "uv",
      "args": [
        "--directory",
        "/ABSOLUTE/PATH/TO/File_Summarizer_MCP_Server/file_summarizer",
        "run",
        "file_summarizer.py"
      ]
    }
  }
}

3. Restart Claude Desktop, and your tools should appear!

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🧪 MCP Tools Provided

Tool Name	Description
read_file	Reads raw content from a file
summarize_file	Summarizes content of any file
summarize_text	Summarizes raw text string
detect_language	Detects the language of input text
translate_text	Translates any text to English
transcribe_file	Transcribe audio or video file content

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📝 Requirements

• Python 3.12
• Apache Tika
• langdetect
• deep-translator
• fastmcp

Install all with:

pip install -r requirements.txt

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📜 License

This project is licensed under the MIT License. See the LICENSE file for details.

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👤 Author

Muskan Raghav