Tempreon — Personal AI Memory vs Compartment

In-depth architectural comparison of the Tempreon — Personal AI Memory and Compartment 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 Tempreon — Personal AI Memory when:

• You need dedicated capabilities in the Knowledge & Memory domain.
• You prefer remote streaming HTTP/SSE transport architecture.
• Your security boundary fits: No auth required (Free / Open Source).

Explore Tempreon — Personal AI Memory Details

Choose Compartment 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 Compartment Details

Feature & Specification Comparison

Specification	Tempreon — Personal AI Memory Knowledge & Memory	Compartment Knowledge & Memory
Summary	Person-owned, portable AI memory as a remote MCP server, readable and writable by any MCP client.	Fully offline, encrypted-at-rest vector memory for AI agents. AEAD-encrypted vectors, no cloud.
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": {
    "tempreon-personal-ai-memory": {
      "url": "https://api.tempreon.com/functions/v1/tempreon-mcp/mcp"
    }
  }
}

{
  "mcpServers": {
    "compartment": {
      "command": "uvx",
      "args": [
        "compartment"
      ]
    }
  }
}

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