MCP Roo Memory vs Mengram

In-depth architectural comparison of the MCP Roo Memory and Mengram MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.

Which MCP Server Should You Choose?

Choose MCP Roo Memory when:

• You need dedicated capabilities in the Knowledge & Memory domain.
• You prefer local stdio subprocess transport architecture.
• Your security boundary fits: No auth required (Free / Open Source).
• Primary tools included: desktop_open, desktop_focus, desktop_history.

Explore MCP Roo Memory Details

Choose Mengram when:

• You need dedicated capabilities in the Knowledge & Memory domain.
• You prefer local stdio subprocess transport architecture.
• Your security boundary fits: API Key required (Freemium).
• You have access to required keys: MENGRAM_API_KEY.
• Primary tools included: Semantic, episodic, and procedural memory types, Procedures evolve from failure feedback, Native multilingual retrieval (23 languages).

Feature & Specification Comparison

Specification	MCP Roo Memory mcasdfgf Knowledge & Memory	Mengram alibaizhanov Knowledge & Memory
Summary	Persistent fractal graph memory for AI coding agents via MCP. Semantic vector search, hot/cold/archive context tiers, decision tracking, and Docker-based deployment with Qdrant.	Human-like memory layer for AI agents with semantic, episodic, and procedural memory. Claude Code hooks (auto-save, auto-recall, cognitive profile). 29 MCP tools, knowledge graph, smart triggers, multi-user isolation. Python & JS SDKs.
Category & Scope

Tools & Capabilities Breakdown

Ready-to-Paste Client Configurations

Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).

{
  "mcpServers": {
    "mcasdfgf-mcp-roo-memory": {
      "command": "npx",
      "args": [
        "-y",
        "mcasdfgf-mcp-roo-memory"
      ]
    }
  }
}

{
  "mcpServers": {
    "alibaizhanov-mengram": {
      "command": "uvx",
      "args": [
        "mengram-ai"
      ],
      "env": {
        "MENGRAM_API_KEY": "YOUR_MENGRAM_API_KEY_HERE"
      }
    }
  }
}

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