What is the key difference between Engram and Lore?

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

How do I install Engram or Lore 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 and Lore free or paid?

Engram operates under a Free / Open Source model (No auth required). Lore operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Engram lists 6 tools with 1 views and 7 GitHub stars. Lore lists 6 tools with 0 views and 7 GitHub stars.

Can I use both Engram and Lore 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.

How do I install Engram or Lore in Claude Desktop, Cursor, or Windsurf?

Both servers follow the standard Model Context Protocol configuration format. Simply copy the JSON block from the configuration section above and paste it into your AI client's mcpServers configuration object (for instance in claude_desktop_config.json or ~/.cursor/mcp.json ), then completely restart or refresh the application.

Are Engram and Lore free to use, or do they require API keys?

Engram is listed under a Free / Open Source model with No auth required . Lore operates under a Free / Open Source model with No auth required . If environment variables are required (such as API keys), be sure to define them under the env key in your MCP client's configuration file.

Can I run both Engram and Lore at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both hbarefoot-engram and hyunjae-labs-lore as distinct keys inside the single mcpServers object in your configuration file. Your AI assistant will automatically select and call the appropriate tool from either server during chat sessions.

Which MCP server has higher directory engagement and quality ratings?

On AllMCPs, Engram has a Quality Score of 55 /100 ( Good ) with 1 views, 0 installs, and 7 GitHub stars. Lore holds a Quality Score of 55 /100 ( Good ) with 0 views, 0 installs, and 7 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Engram vs Lore

In-depth architectural comparison of the Engram and Lore 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

Knowledge & Memory · Local stdio

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

Lore

Knowledge & Memory · Local stdio

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

Verdict Summary: Choose Engram if you need specialized Knowledge & Memory tools running via a local process. Choose Lore 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 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: engram_remember, engram_recall, engram_forget.

Explore Engram Details

Choose Lore 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: manage_projects, index, status.

Explore Lore Details

Feature & Specification Comparison

Specification	Engram HBarefoot Knowledge & Memory	Lore hyunjae-labs Knowledge & Memory
Summary	Local-first persistent memory for AI agents. SQLite + local embeddings (all-MiniLM-L6-v2), hybrid semantic + FTS5 recall, secret detection, and contradiction handling. 6 MCP tools (remember, recall, forget, feedback, context, status) over stdio. Zero cloud, no API keys, fully offline. Works with Claude Desktop/Code, Cursor, and Windsurf. npm install -g @hbarefoot/engram	Semantic search across Claude Code conversations. Hybrid vector + keyword search with Reciprocal Rank Fusion, fully local, background indexing, project-selective.
Category & Scope

Tools & Capabilities Breakdown

Engram Tools (6)

engram_remember

Store a memory with category, entity, confidence, namespace, tags. Auto-runs secret detection.

engram_recall

Hybrid semantic + FTS5 search. Supports `category`, `namespace`, `threshold`, and `time_filter`.

engram_forget

Delete a specific memory by ID.

engram_feedback

Vote a memory helpful/unhelpful. Drives the feedback loop above.

engram_context

Pre-formatted context block (`markdown` / `xml` / `json` / `plain`) with a token budget for system-prompt injection.

engram_status

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 Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "hbarefoot-engram": {
      "command": "npx",
      "args": [
        "-y",
        "hbarefoot-engram"
      ]
    }
  }
}

Lore Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "hyunjae-labs-lore": {
      "command": "npx",
      "args": [
        "-y",
        "getlore"
      ]
    }
  }
}

Frequently Asked Questions

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

More alternatives to Engram More alternatives to Lore Knowledge & Memory category hub