Process and Analyze PDF Documents
AI-powered MCP server for advanced PDF text extraction, search, and metadata retrieval with customizable options.
Maintainer of this project? Claim this page to edit the listing.
1.0.0Add to Favorites
Why it matters
Automate the extraction, searching, and analysis of text and metadata from local PDF files. This asset provides a robust server for integrating advanced PDF processing capabilities into your applications.
Outcomes
What it gets done
Extract text content from specified PDF pages or entire documents.
Search for specific text patterns within PDF files using flexible search options.
Retrieve detailed metadata, including author, title, and creation dates.
Clean and normalize extracted text for further processing.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/vb-pdf-reader-mcp | bash Capabilities
Tools your agent gets
Extract text from PDF files with customizable options including page ranges and metadata.
Search for specific text in PDF documents with case sensitivity, whole words, and regex options.
Retrieve comprehensive metadata from PDF files including author, title, creation date, and keywords.
Overview
PDF Reader MCP Server
This MCP server provides advanced PDF processing capabilities. It offers tools for extracting text content with options for page ranges and text cleaning, searching for specific text within documents using case-sensitive and whole-word matching, and retrieving comprehensive metadata such as author, title, and creation dates. The server also includes features like file size limits and asynchronous processing for efficient operation. Use this MCP server when you need to integrate PDF data extraction, search, or metadata retrieval into an AI client or workflow. It is ideal for tasks requiring programmatic access to information contained within PDF files, such as document analysis, information retrieval, or content summarization.
What it does
The big job is to efficiently process and extract information from PDF documents to support AI-driven analysis and workflows. The small job is to provide a robust MCP server that exposes tools for reading, searching, and retrieving metadata from PDFs. For example, to install this server, you would run:
npm install
And to extract text from a PDF with clean text enabled and metadata excluded, you would use the following parameters:
{
"file": "/path/to/document.pdf",
"clean_text": true,
"include_metadata": false
}
Source README
MCP PDF Reader Enhanced
A comprehensive Model Context Protocol (MCP) server that provides advanced PDF text extraction, search, and analysis functionality.
Features
Core Functionality
- ✅ Text Extraction: Extract text content from PDF files with customizable options
- ✅ Text Search: Search for specific text within PDFs with advanced options
- ✅ Metadata Extraction: Retrieve comprehensive PDF metadata
- ✅ Page-specific Processing: Extract content from specific page ranges
- ✅ Text Cleaning: Normalize and clean extracted text
- ✅ File Size Limits: Protection against overly large files (50MB limit)
- ✅ Async Processing: Non-blocking file operations
Advanced Features
- 🔄 Multiple Tools: 3 specialized tools for different PDF operations
- 🔍 Smart Search: Case-sensitive, whole-word, and regex search options
- 📊 Rich Metadata: Extract author, title, creation date, keywords, and more
- ⚡ Performance: Efficient processing with size limits and error handling
- 🛡️ Security: File validation and path sanitization
Installation
npm install
Tools Available
1. read-pdf - Enhanced PDF Reading
Extract text from PDF files with customizable options.
Parameters:
file(string, required): Path to the PDF filepages(string, optional): Page range (e.g., '1-5', '1,3,5', 'all'). Default: 'all'include_metadata(boolean, optional): Include PDF metadata. Default: trueclean_text(boolean, optional): Clean and normalize text. Default: false
Example Usage:
// Basic extraction
{ "file": "/path/to/document.pdf" }
// Extract with clean text and no metadata
{
"file": "/path/to/document.pdf",
"clean_text": true,
"include_metadata": false
}
2. search-pdf - Search Within PDFs
Search for specific text within PDF documents.
Parameters:
file(string, required): Path to the PDF filequery(string, required): Text to search forcase_sensitive(boolean, optional): Case sensitive search. Default: falsewhole_word(boolean, optional): Match whole words only. Default: false
Example Usage:
// Case-insensitive search
{ "file": "/path/to/document.pdf", "query": "important term" }
// Whole word, case-sensitive search
{
"file": "/path/to/document.pdf",
"query": "API",
"case_sensitive": true,
"whole_word": true
}
3. pdf-metadata - Extract Metadata Only
Get comprehensive metadata from PDF files without extracting text.
Parameters:
file(string, required): Path to the PDF file
Returns:
- Filename, file size, page count
- Author, title, subject, creator, producer
- Creation/modification dates, keywords
- Encryption status, PDF version
Configuration
Cursor Integration
Add to your Cursor settings:
{
"mcpServers": {
"mcp-gp-pdf-reader": {
"command": "node",
"args": ["/absolute/path/to/mcp_gp_pdf_reader/index.js"]
}
}
}
Future Enhancements
Planned Features
- 🔮 OCR Support: Extract text from scanned/image-based PDFs
- 🔮 Image Extraction: Extract images from PDF documents
- 🔮 Table Detection: Identify and extract tabular data
- 🔮 Form Data: Extract form fields and values
- 🔮 Password Support: Handle password-protected PDFs
- 🔮 Batch Processing: Process multiple PDFs simultaneously
- 🔮 Caching: Cache parsed results for better performance
- 🔮 Page-by-Page: True page-specific text extraction
Technical Improvements
- 🔧 Streaming: Handle very large PDFs with streaming
- 🔧 Progress Tracking: Progress indicators for long operations
- 🔧 Resource Management: Better memory usage optimization
- 🔧 Configuration API: Runtime configuration updates
Usage Examples
Basic Text Extraction
# Via MCP client
"Extract all text from /documents/report.pdf"
Searching PDFs
# Via MCP client
"Search for 'quarterly results' in /documents/financial-report.pdf"
Getting Metadata
# Via MCP client
"Get metadata from /documents/contract.pdf"
Development
Requirements
- Node.js 18.0.0 or higher
- Memory: Sufficient for PDF file size + processing overhead
- Storage: Temporary space for file operations
FAQ
Common questions
Discussion
Questions & comments · 0
Sign In Sign in to leave a comment.