koraynar/doc-extract-mcp

Overview

MCP server that gives an AI assistant deterministic document tooling. It provides PDF and text reading, chunking, JSON Schema validation, and structured output. Access is path-confined and the implementation is fully tested.

Best for

Best for
Developers building AI assistants that need safe, structured document processing

Use cases

• Extract text from PDFs and text files within a sandboxed path
• Validate document-derived data against JSON Schema
• Generate structured output from documents for AI workflows

Notes

MCP server that gives an AI assistant deterministic document tooling. It provides PDF and text reading, chunking, JSON Schema validation, and structured output. Access is path-confined and the implementation is fully tested.

0 stars on GitHub. Last updated 2026-08-28. Licensed MIT.

Use cases

• Extract text from PDFs and text files within a sandboxed path
• Validate document-derived data against JSON Schema
• Generate structured output from documents for AI workflows

Pros

• Path confinement reduces the risk of unintended file access
• Deterministic behavior makes output predictable and reproducible
• Fully tested implementation for core document operations

Cons

• Zero stars indicate little community adoption or validation yet
• Requires a Python runtime to deploy
• Scope is limited to document tooling, not general file or system access

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.