Build interactive PDF text extraction from Amazon S3
Machine Learning Blog
This article demonstrates how to build an MCP server for real-time PDF text extraction from Amazon S3, offering an interactive alternative to batch processing for compliance, legal, and financial teams.
- Use Model Context Protocol (MCP) to connect AI assistants directly to text-based PDFs in S3 for on-demand queries
- Ideal for interactive workflows where batch processing is too slow; not suitable for scanned documents or OCR needs
- Costs approximately $2.50/month for 10,000 text-based PDF pages versus $23-28 with Amazon Textract
- Includes step-by-step Python implementation using boto3, PyPDF2, and Kiro CLI integration
- Leverages existing AWS IAM credentials with least-privilege S3 read access and automatic temporary file cleanup
- Processes typical 50-page PDFs in seconds with linear scaling; limited to text extraction without layout or form understanding
- Real-world use cases include legal contract searches during client calls, compliance policy lookups during audits, and executive data queries in meetings
The MCP server pattern provides a lightweight, cost-effective solution for interactive PDF text extraction, complementing Amazon Textract for complex document processing at scale.
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