RCLL vs Iai Personal Memory Engine

In-depth architectural comparison of the RCLL and Iai Personal Memory Engine 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?

R

Choose RCLL 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).
• Primary tools included: memory_retain, memory_recall, memory_reflect.

Explore RCLL Details

Choose Iai Personal Memory Engine 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: memory_recall, memory_temporal_recall, memory_recall_structural.

Explore Iai Personal Memory Engine Details

Feature & Specification Comparison

Specification	R RCLL Knowledge & Memory	Iai Personal Memory Engine CodeAbra Knowledge & Memory
Summary	Self-hosted shared memory for a team of AI agents. Rooms, L0-L3 depth, no LLM on the read path.	Local memory daemon for any MCP-over-stdio client with three-tier storage (episodic/semantic/procedural). Own SQLite + hnswlib store (Hippo) with bge-small-en-v1.5, MIT-licensed community-detection reranking (MOSAIC), and sleep-cycle consolidation. AES-256-GCM encrypted at rest, no telemetry. Verbatim recall >=99% and post-contradiction Rescue@10 1.000 at honest scale. Ambient capture via shell hooks. Windows support in beta.
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": {
    "rcll": {
      "url": "https://godcrm.ai/git/holetron-lab/fleet-memory"
    }
  }
}

{
  "mcpServers": {
    "codeabra-iai-personal-memory-engine": {
      "command": "uvx",
      "args": [
        "iai-pme"
      ]
    }
  }
}

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