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DocReaderMCP Server

by prafulsapkota
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Python
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DocReaderMCP Server

A FastMCP server designed to read and stream various file formats commonly used in organizations (PDF, DOCX, Excel XLSX, CSV, TSV, TXT). It outputs formatted Markdown and supports both segment/page limits and item streaming.

Features

  • Document Formats Supported:

    • PDF: Pages parsed and converted to text.

    • DOCX: Paragraphs segmented into logical page blocks.

    • Excel (XLSX/XLS): Targeted sheet names or first sheet parsed.

    • CSV & TSV: Tables outputted in Markdown format.

    • TXT: Plain text paginated into logical blocks.

  • Reading Options:

    • Optional page_range parameter (e.g. 1-3, 2) to select specific pages.

    • Optional sheet_name parameter for Excel files.

  • Streaming Options:

    • Text-Style Documents (PDF, DOCX, TXT): Streamed sentence-by-sentence.

    • Tabular Documents (Excel, CSV, TSV): Streamed row-by-row as Markdown table rows.

  • Docker Ready: Built with python:3.13.3-slim.

Related MCP server: groupdocs-markdown-mcp

Tools Reference

Tool Name

Parameters

Description

read_pdf

file_path (str), page_range (Optional[str])

Read PDF file pages

stream_pdf

file_path (str), page_range (Optional[str])

Stream PDF sentences

read_docx

file_path (str), page_range (Optional[str])

Read DOCX paragraphs by page

stream_docx

file_path (str), page_range (Optional[str])

Stream DOCX sentences

read_excel

file_path (str), sheet_name (Optional[str])

Read sheet to Markdown table

stream_excel

file_path (str), sheet_name (Optional[str])

Stream sheet row-by-row

read_csv

file_path (str)

Read CSV to Markdown table

stream_csv

file_path (str)

Stream CSV row-by-row

read_tsv

file_path (str)

Read TSV to Markdown table

stream_tsv

file_path (str)

Stream TSV row-by-row

read_txt

file_path (str), page_range (Optional[str])

Read TXT by page

stream_txt

file_path (str), page_range (Optional[str])

Stream TXT sentences

Installation & Setup

Local Run (Venv / System Python)

  1. Install dependencies:

    pip install -r requirements.txt

  2. Start the server in standard mode:

    python main.py run

    Or in development mode:

    python main.py dev

Running with Docker

  1. Build and start the container:

    docker compose up --build

  2. By default, the container mounts a local ./data directory to /data in the container. Put your organizational documents in ./data to read them via the container.

This server cannot be deployed

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Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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