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Parse PDFs into Structured Data

Parse local or remote PDF files into structured JSON or Markdown using NetMind's PDF parsing AI service.

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Works with cursorclaudewindsurf
Protagolabs
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86
Spark score
out of 100
Updated Jun 2025
Fresher alternatives ↓
Version 0.1.6
Models
universal
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Why it matters

Leverage AI to reliably extract and convert information from PDF documents into structured formats like JSON or Markdown. This service supports both local files and remote URLs, making it ideal for integrating PDF data into AI agents and applications.

Outcomes

What it gets done

01

Convert PDF content to JSON or Markdown.

02

Process PDFs from local file paths or remote URLs.

03

Provide structured data output for AI agent integration.

04

Extract key information from PDF documents.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-netmind-parsepro | bash

Capabilities

Tools your agent gets

parse_pdf

Parses a PDF file and returns extracted content in JSON or Markdown format from local files or remote URLs.

Overview

NetMind ParsePro MCP Server

NetMind ParsePro parses local or remote PDF files into structured JSON or Markdown through a single parse_pdf tool, backed by NetMind's PDF Parser AI service and requiring a NetMind API token. Use it when an AI assistant needs to extract PDF content as structured JSON or Markdown. Requires a NetMind API token to authenticate.

What it does

NetMind ParsePro is an MCP server wrapping NetMind's PDF Parser AI service, converting PDF files into structured JSON or Markdown so an AI agent can work with their content directly instead of handling raw PDF bytes.

When to use - and when NOT to

Use it when you need an AI assistant to extract and reformat content from a PDF - whether stored locally or hosted at a remote URL - into structured JSON for programmatic use or Markdown for readable text. Do not use it without a NetMind API token, which the server requires to authenticate parsing requests; get one from netmind.ai/user/apiToken.

Capabilities

  • parse_pdf: parses a PDF and returns its extracted content in a specified format.
    • source (required): either a remote URL (starting with http:// or https://) or a local file path (absolute path recommended).
    • format: "json" (structured dictionary) or "markdown" (formatted text string).

How to install

Requires uv:

brew install uv
# or
curl -LsSf https://astral.sh/uv/install.sh | sh

Get an API token from netmind.ai/user/apiToken, then configure Cursor, Claude Desktop, or Windsurf:

{
  "mcpServers": {
    "parse-pdf": {
      "env": { "NETMIND_API_TOKEN": "XXXXXXXXXXXXXXXXXXXX" },
      "command": "uvx",
      "args": ["netmind-parse-pdf-mcp"]
    }
  }
}

Config file locations: Cursor (~/.cursor/mcp.json or %APPDATA%\Cursor\mcp.json equivalents), Claude Desktop (claude_desktop_config.json), Windsurf (~/.codeium/windsurf/mcp_config.json).

Who it's for

Developers and researchers who need to feed PDF content (local files or URLs) into an AI workflow as clean structured JSON or Markdown instead of parsing PDFs manually.

Source README

NetMind ParsePro

The PDF Parser AI service, built and customized by the NetMind team, is a high-quality, robust,
and cost-efficient solution for converting PDF files into specified output formats such as JSON and Markdown.
It is fully MCP server-ready, allowing seamless integration with AI agents.

Components

Tools

  • parse_pdf: Parses a PDF file and returns the extracted content in the specified format.
    The tools supports both local file paths and remote URLs as input sources.
    It extracts the content from the PDF and formats it either as structured JSON or as a Markdown string.
    • source: required: The source of the PDF file to be parsed.
      • If it is a string starting with "http://" or "https://", it will be treated as a remote URL.
      • Otherwise, it will be treated as a local file path (absolute path recommended, e.g. "/Users/yourname/file.pdf").
    • format: the desired format for the parsed output. Supports: "json", "markdown"
    • Returns the extracted content in the specified format (JSON dictionary or Markdown string).

Installation

Requires UV (Fast Python package and project manager)

If uv isn't installed.

# Using Homebrew on macOS
brew install uv

or

# On macOS and Linux.
curl -LsSf https://astral.sh/uv/install.sh | sh

# On Windows.
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Environment Variables

You can obtain an API key from Netmind

  • NETMIND_API_TOKEN: Your Netmind API key

Cursor & Claude Desktop && Windsurf Installation

Add this tool as a mcp server by editing the Cursor/Claude/Windsurf config file.

{
  "mcpServers": {
    "parse-pdf": {
      "env": {
        "NETMIND_API_TOKEN": "XXXXXXXXXXXXXXXXXXXX"
      },
      "command": "uvx",
      "args": [
        "netmind-parse-pdf-mcp"
      ]
    }
  }
}
Cursor
  • On MacOS: /Users/your-username/.cursor/mcp.json
  • On Windows: C:\Users\your-username\.cursor\mcp.json
Claude
  • On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
  • On Windows: %APPDATA%/Claude/claude_desktop_config.json

Windsurf

  • On MacOS: /Users/your-username/.codeium/windsurf/mcp_config.json
  • On Windows: C:\Users\your-username\.codeium\windsurf\mcp_config.json

FAQ

Common questions

Discussion

Questions & comments · 0

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