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ultimate_mcp_server vs pfc-mcp

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

ultimate_mcp_server
by Dicklesworthstone
pfc-mcp
by yusong652
Stars★ 149★ 37
30d uses
Score8544
Official
Categories
AI / LLM ToolsBrowser AutomationFile System
Developer ToolsAI / LLM ToolsProductivity
LanguagePythonPython
Last commit2 mo agothis month

ultimate_mcp_server · Summary

Comprehensive MCP server providing dozens of capabilities for AI agents including LLM delegation, browser automation, document processing, and cognitive memory systems.

pfc-mcp · Summary

MCP server connecting AI agents to ITASCA PFC for running DEM simulations through natural conversation.

ultimate_mcp_server · Use cases

  • Complex document processing and analysis with OCR and structured data extraction
  • Web automation and research across multiple sites with browser control
  • Cost-optimized AI workflows through intelligent task delegation between models

pfc-mcp · Use cases

  • Automating DEM simulations through conversational AI interfaces
  • Assisting researchers with PFC command documentation and usage examples
  • Enabling remote control and monitoring of simulation tasks

ultimate_mcp_server · Install

Installation

  1. Clone the repository:
git clone https://github.com/Dicklesworthstone/ultimate_mcp_server.git
cd ultimate_mcp_server
  1. Install dependencies:
pip install -e .
  1. For Claude Desktop integration, add to your claude_desktop_config.json:
{
  "mcpServers": {
    "ultimate-mcp": {
      "command": "python",
      "args": ["-m", "ultimate_mcp_server"],
      "env": {
        "PYTHONPATH": "."
      }
    }
  }
}
  1. Run the server:
python -m ultimate_mcp_server

pfc-mcp · Install

Prerequisites

  • ITASCA PFC 6.0, 7.0, or 9.0 installed
  • [uv](https://docs.astral.sh/uv/getting-started/installation/) installed

Setup

  1. Register the MCP server in your client config:
{
  "mcpServers": {
    "pfc-mcp": {
      "command": "uvx",
      "args": ["pfc-mcp"]
    }
  }
}
  1. Start the bridge from inside PFC by downloading and running [addon.py](addon.py)
Comparison generated from public README + GitHub signals. Last updated automatically.