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everything vs nutrient-dws-mcp-server

Side-by-side comparison to help you pick between these two MCP servers.

everything
by modelcontextprotocol
nutrient-dws-mcp-server
by PSPDFKit
Stars★ 85,748★ 63
30d uses
Score7746
Official
Categories
Developer ToolsAI / LLM ToolsOther
Developer ToolsAI / LLM ToolsProductivity
LanguageTypeScriptTypeScript
Last committhis month2 mo ago

everything · Summary

Official MCP test server exercising all protocol features for client builders.

nutrient-dws-mcp-server · Summary

MCP server connecting AI agents to PDF processing capabilities via Nutrient DWS API for document manipulation.

everything · Use cases

  • Testing MCP client implementations against all protocol features
  • Learning MCP protocol capabilities through a reference server
  • Validating client compatibility with different transport methods

nutrient-dws-mcp-server · Use cases

  • Converting document formats through natural language commands
  • Automating document redaction of sensitive information
  • Digitally signing PDF documents with visible signatures

everything · Install

NPX (recommended)

{
  "mcpServers": {
    "everything": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-everything"]
    }
  }
}

On Windows, use cmd /c:

{
  "mcpServers": {
    "everything": {
      "command": "cmd",
      "args": ["/c", "npx", "-y", "@modelcontextprotocol/server-everything"]
    }
  }
}

Docker

{
  "mcpServers": {
    "everything": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "mcp/everything"]
    }
  }
}

Global install

npm install -g @modelcontextprotocol/server-everything@latest
npx @modelcontextprotocol/server-everything

nutrient-dws-mcp-server · Install

Installation

  1. Create a Nutrient account at [nutrient.io/api](https://dashboard.nutrient.io/sign_up/)
  2. Configure your AI client with the following settings:
Claude Desktop
{
  "mcpServers": {
    "nutrient-dws": {
      "command": "npx",
      "args": ["-y", "@nutrient-sdk/dws-mcp-server"],
      "env": {
        "SANDBOX_PATH": "/your/sandbox/directory"
      }
    }
  }
}
  1. Restart your AI client and place documents in your sandbox directory
Comparison generated from public README + GitHub signals. Last updated automatically.