PDF Reader MCP Server (@shtse8/pdf-reader-mcp)

@shtse8

Basic information

About PDF Reader MCP Server

📄 The PDF intelligence layer for AI agents — Agent Document Twin, evidence-first extraction, visual crops, OCR provenance, trust reports, and benchmark-gated releases. MCP server for Claude, Cursor, VS Code, and any MCP client.

#nodejs #pdf #typescript #mcp #stdio #pdf-reader #pdf-parser#pdf-parse#ai-agent#model-content-protocol#llm-tool

PDF Reader MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "pdf-reader-mcp": {
      "command": "npx",
      "args": [
        "@sylphx/pdf-reader-mcp"
      ]
    }
  }
}

PDF Reader MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

Fetch the live tool list by running this server in a temporary sandbox using the button above.

Overview

What is PDF Reader MCP Server?

PDF Reader MCP Server transforms PDFs into an Agent Document Twin: a linked, source-backed representation that AI agents can inspect, search, verify, crop, OCR, enrich, cite, and read with confidence. It is built for agents that need evidence and provenance, not just extracted text.

How to use PDF Reader MCP Server?

Install and run via npx: npx @sylphx/pdf-reader-mcp. Node.js 22.13 or higher is required. For Claude Desktop, add a configuration entry with the same command. A Docker image is also available from GitHub Container Registry. The default package works without any OCR models, vision models, or cloud credentials.

Key features of PDF Reader MCP Server

One smart tool (read_pdf) that auto-inspects and reads PDFs
Multi-layered Agent Document Twin: lossless PDF, visual, semantic, evidence, and agent layers
Optional OCR and visual region analysis via provider adapters
Built-in trust and accessibility reports for safety
Evidence-first extraction with page numbers, bounding boxes, and crop IDs
Benchmark-gated releases with deterministic quality checks