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mcp_documents_reader

Active·★ 21·MIT·Updated 2026-03-13
★ Hidden Gem★ RAG / Knowledge Base

Model Context Protocol (MCP) server exposes tools to read multiple document types including DOCX, PDF, Excel, and TXT. This has been tested on Trae Desktop.

The MCP Document Reader is a powerful tool designed to enable AI agents to truly 'read' documents by supporting various formats. It acts as an MCP-compliant interface for extracting text content from Excel, DOCX, PDF, and TXT files, facilitating integration with AI assistants.

#MCP#Document Reader#AI Agents#Multi-format#Python#Text Extraction#File System#Tooling
$ Install
$ pip install mcp-documents-reader
↗ Visit site★ GitHub
01

Features

01Multi-format Support
02MCP Protocol Compliant
03Easy Integration
04Reliable Performance
05File System Support
02

Compatibility

Python
Runtime
Verified via docs
MCP Protocol
Standard
Verified via docs
Trae IDE
Platform
Verified via docs
03

Quick start

1
$ pip install mcp-documents-reader
04

Use cases

↳Enabling AI agents to 'read' and process document content.
↳Integrating document reading capabilities into AI assistants, like Trae IDE.
↳Extracting text from various document types for AI analysis or knowledge retrieval.
05

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mcp_documents_reader AlternativesBest RAG / Knowledge Base Tools 2026Open Source RAG / Knowledge Basemcp_documents_reader Tutorialmcp_documents_reader Vs CompetitorsMCPDocument ReaderAI Agents

Comments

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  • E
    Elliot ZhangMay 11, 2026

    Works reliably for the common office document formats.

  • T
    Taylor ThompsonMay 2, 2026

    Consistent output format across document types makes downstream processing cleaner.

  • Oaklyn Rivera
    Oaklyn RiveraMar 24, 2026

    Good for AI workflows that need to process diverse document types.

  • M
    Marlowe NguyenMar 23, 2026

    Multi-format document reading via MCP — PDF, Word, Excel without custom parsers.

On this page
01Features02Compatibility03Quick start04Use cases05Alternatives
Stats
GitHub Stars★ 21
Last commit2mo ago
StatusActive
LicenseMIT
CategoryRAG / Knowledge Base
Trend (30d)
+0.8↑ 0.4%
Links
Documentation↗Discussion↗Issues↗Releases↗

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