File_Summarizer_MCP_Server
@Muskan244
File_Summarizer_MCP_Server について
Claude-compatible tool to read and summarize files using Apache Tika and MCP protocol
基本情報
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ツール
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概要
What is File_Summarizer_MCP_Server?
File_Summarizer_MCP_Server is a lightweight server built using the Model Context Protocol (MCP) to read and summarize content from various file formats via Apache Tika. It supports summarization of both raw text and file content, and exposes additional MCP tools for language detection and translation, making it suitable for integration into AI workflows.
How to use File_Summarizer_MCP_Server?
The README does not provide installation, configuration, or invocation instructions. The server is built with Python 3.12 and the FastMCP server framework, and exposes async MCP tools for summarization, language detection, and translation.
Key features of File_Summarizer_MCP_Server
- Reads content from any file type supported by Apache Tika (PDF, DOCX, TXT, etc.)
- Summarizes file content or raw input text
- Exposes async MCP tools for language detection and translation
- Built with Python 3.12 and FastMCP framework
- Ready for use with LLMs or other AI systems
Use cases of File_Summarizer_MCP_Server
- Summarize PDF or DOCX documents for quick overviews
- Detect the language of input text or file content
- Translate text as part of a multi-step AI pipeline
- Integrate file summarization into MCP-powered assistants
FAQ from File_Summarizer_MCP_Server
What file formats are supported?
Any file type supported by Apache Tika – including PDF, DOCX, TXT, and many others.
Does File_Summarizer_MCP_Server require Apache Tika to be installed?
The README states it uses Apache Tika to read content, but does not specify whether Tika must be separately installed or is bundled.
What programming language and framework is it built with?
It is built with Python 3.12 and the FastMCP server framework.
What tools does File_Summarizer_MCP_Server expose?
It exposes async MCP tools for summarization (of files or raw text), language detection, and translation.
Is File_Summarizer_MCP_Server ready for AI workflows?
Yes, it is designed for easy integration with LLMs and other AI systems via the Model Context Protocol.
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