Montycat MCP — Shared AI Memory vs Stremai

In-depth architectural comparison of the Montycat MCP — Shared AI Memory and Stremai 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?

M

Choose Montycat MCP — Shared AI 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).

Explore Montycat MCP — Shared AI Memory Details

Choose Stremai 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).

Explore Stremai Details

Feature & Specification Comparison

Specification	M Montycat MCP — Shared AI Memory Knowledge & Memory	Stremai Knowledge & Memory
Summary	One shared, persistent memory across AI agents and systems, with semantic recall and live updates.	Shared memory for AI coding agents. Connected agents can recall across Claude Code, Codex, Cursor.
Category & Scope	Knowledge & Memory	Knowledge & Memory

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": {
    "montycat-mcp-shared-ai-memory": {
      "command": "uvx",
      "args": [
        "montycat-mcp"
      ]
    }
  }
}

{
  "mcpServers": {
    "stremai": {
      "command": "npx",
      "args": [
        "-y",
        "aiagentsbay-mcp@latest"
      ]
    }
  }
}

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