What is the key difference between Engram Rs and Lean Memory?

Engram Rs belongs to the Knowledge & Memory category with local stdio execution, while Lean Memory belongs to the Knowledge & Memory category with local stdio execution.

How do I install Engram Rs or Lean Memory in Claude Desktop or Cursor?

Copy the mcpServers JSON configuration snippet provided on this page into your claude_desktop_config.json or ~/.cursor/mcp.json file and restart your AI client.

Are Engram Rs and Lean Memory free or paid?

Engram Rs operates under a BYOK (Pay Provider Direct) model (API Key required). Lean Memory operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Engram Rs lists 16 tools with 2 views and 27 GitHub stars. Lean Memory lists 6 tools with 2 views and 42 GitHub stars.

Can I use both Engram Rs and Lean Memory together in the same MCP host?

Yes! MCP hosts like Claude Desktop, Cursor, Windsurf, Cline, and VS Code support configuring multiple servers under the mcpServers object simultaneously.

Side-by-Side Model Context Protocol Comparison

Engram Rs vs Lean Memory

In-depth architectural comparison of the Engram Rs and Lean Memory 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.

At a Glance & Executive Verdict

Engram Rs

Knowledge & Memory · Local stdio

Quality: 57/100 (Good) | Auth: API Key required

Lean Memory

Knowledge & Memory · Local stdio

Quality: 55/100 (Good) | Auth: No auth required

Verdict Summary: Choose Engram Rs if you need specialized Knowledge & Memory tools running via a local process. Choose Lean Memory if your workspace requires Knowledge & Memory integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.

Which MCP Server Should You Choose?

Choose Engram Rs when:

You need dedicated capabilities in the Knowledge & Memory domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: API Key required (BYOK (Pay Provider Direct)).
You have access to required keys: ENGRAM_EMBEDDING_PROVIDER, ENGRAM_EMBEDDING_API_KEY.
Primary tools included: engram_store, engram_recall, engram_recent.

Explore Engram Rs Details

Choose Lean 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).
You have access to required keys: LM_DATA_ROOT, ANTHROPIC_API_KEY.
Primary tools included: Single SQLite file per namespace for isolated memory storage, Hybrid dense (embedding) and sparse (FTS5) search retrieval, Add-only memory history with point-in-time querying.

Feature & Specification Comparison

Specification	Engram Rs kael-bit Knowledge & Memory	Lean Memory Wuesteon Knowledge & Memory
Summary	Hierarchical memory engine for AI agents with automatic decay, promotion, semantic dedup, and self-organizing topic tree. Single Rust binary, zero external dependencies.	Embedded, local-first agent memory in a single SQLite file per namespace (vec0 + FTS5 hybrid retrieval). ADD-only history queryable as-of any past time; offline sleep-time maintenance stages dedupe/summarize/evict proposals a human reviews. No Docker, no server, no cloud key. pip install 'lean-memory[mcp]'
Category & Scope

Tools & Capabilities Breakdown

Engram Rs Tools (16)

engram_store

Store a memory. All memories start in Buffer and promote to Working/Core through access frequency and LLM quality gating. Procedural memories and lessons (tag=lesson) auto-promote to Working after 2h. Use supersedes to replace outdated memories by their ids.

engram_recall

Hybrid semantic + keyword search with budget-aware retrieval. Fast by default (~30ms cached, ~1s first query). Optional expand adds LLM query expansion (+1-2s) — only use for short/vague queries.

engram_recent

List recent memories by creation time. Good for session context recovery.

engram_resume

Full memory bootstrap for session recovery. Returns core (permanent knowledge), working (ongoing context/decisions), buffer (transient), recent activity, and session notes. Use workspace tags to filter by current work context. Compact mode (default) minimizes token usage.

engram_extract

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).

Engram Rs Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "kael-bit-engram-rs": {
      "command": "npx",
      "args": [
        "-y",
        "engram-rs-mcp"
      ],
      "env": {
        "ENGRAM_EMBEDDING_PROVIDER": "YOUR_ENGRAM_EMBEDDING_PROVIDER_HERE",
        "ENGRAM_EMBEDDING_API_KEY": "YOUR_ENGRAM_EMBEDDING_API_KEY_HERE"
      }
    }
  }
}

Lean Memory Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "wuesteon-lean-memory": {
      "command": "uvx",
      "args": [
        "lean-memory"
      ],
      "env": {
        "LM_DATA_ROOT": "YOUR_LM_DATA_ROOT_HERE",
        "ANTHROPIC_API_KEY": "YOUR_ANTHROPIC_API_KEY_HERE"
      }
    }
  }
}

Frequently Asked Questions

Engram Rs is categorized under Knowledge & Memory and uses a local stdio subprocess. In contrast, Lean Memory belongs to Knowledge & Memory using local stdio subprocess. Select Engram Rs when you need capabilities focused on knowledge & memory and Lean Memory when you require tools for knowledge & memory.

More alternatives to Engram Rs More alternatives to Lean Memory Knowledge & Memory category hub