📄 File Summarizer MCP Server

A fully offline, multi-modal file summarization server built with FastMCP. Supports text, documents, audio, and video files with language detection, translation, and speech-to-text capabilities.

🚀 Features

• 📂 Reads multiple file types — PDF, DOCX, TXT, audio (MP3, WAV), video (MP4, MOV) via Apache Tika & Whisper.
• 🧠 Summarizes file content or raw input text automatically.
• 🌐 Multi-language support — detects input language, translates to English if needed, or keeps summary in original language.
• 🎙 Speech-to-text transcription — audio/video files transcribed via Whisper before summarization.
• ⚙️ Simple async MCP tools — easy to extend and integrate with any MCP client.
• 🔒 Fully offline capable — no need for external LLM APIs.
• 🐍 Built with Python 3.12, FastMCP server framework, Apache Tika, Whisper, LangDetect, and Deep Translator.

🛠 Installation

1️⃣ Clone the repo:

git clone https://github.com/Muskan244/File_Summarizer_MCP_Server.git
cd File_Summarizer_MCP_Server

2️⃣ Setup virtual environment:

python3.12 -m venv .venv
source .venv/bin/activate

3️⃣ Install dependencies:

pip install -r requirements.txt
# Whisper requires ffmpeg installed system-wide
brew install ffmpeg  # (Mac)

🔧 Usage

Start the MCP server:

uv run file_summarizer.py

It exposes the following tools:

• read_file(file_path)
• summarize_file(file_path)
• summarize_text(text)
• detect_language(text)
• translate_text(text)
• transcribe_file(file_path)

You can invoke these via any MCP-compliant client (Claude Desktop, Open Interpreter, etc.).