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memory vs mingli-mcp

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

memory
by modelcontextprotocol
mingli-mcp
by spyfree
Stars★ 85,748★ 2
30d uses
Score7738
Official
Categories
Knowledge GraphAI / LLM ToolsProductivity
AI / LLM ToolsOther
LanguageTypeScriptPython
Last committhis month2 mo ago

memory · Summary

An MCP server implementing persistent memory using a local knowledge graph for AI models to remember user information across chats.

mingli-mcp · Summary

A feature-rich fortune telling MCP server supporting Zi Wei Doushu, Bazi, and planned astrology systems with multi-language output.

memory · Use cases

  • Personalizing AI assistant interactions by remembering user preferences, history, and relationships
  • Building context-aware chat applications that maintain conversation history
  • Creating knowledge bases that persist across AI model sessions

mingli-mcp · Use cases

  • Fortune tellers can use it to quickly generate birth charts and analysis for clients
  • AI assistants can provide personalized fortune analysis through MCP integration
  • Developers can integrate fortune-telling capabilities into their applications
  • Users can get multi-dimensional life insights through various palace analyses

memory · Install

Installation

Claude Desktop

Add to your claude_desktop_config.json:

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

VS Code

Use one-click installation buttons or manually configure in .vscode/mcp.json:

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

Docker

{
  "mcpServers": {
    "memory": {
      "command": "docker",
      "args": ["run", "-i", "-v", "claude-memory:/app/dist", "--rm", "mcp/memory"]
    }
  }
}

mingli-mcp · Install

Installation

Using uvx (Recommended)

Add to your MCP configuration:

{
  "mcpServers": {
    "mingli": {
      "command": "uvx",
      "args": ["mingli-mcp"],
      "env": {
        "LOG_LEVEL": "INFO"
      }
    }
  }
}

From source

git clone https://github.com/spyfree/mingli-mcp
cd mingli-mcp
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Then configure your MCP client to use:

{
  "mcpServers": {
    "mingli": {
      "command": "/path/to/venv/bin/python",
      "args": ["/path/to/mingli_mcp.py"]
    }
  }
}
Comparison generated from public README + GitHub signals. Last updated automatically.