What is the key difference between Engram and Memora?

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

How do I install Engram or Memora 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 Memora free or paid?

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

Which MCP server has more tools and community activity?

Engram lists 6 tools with 2 views and 8 GitHub stars. Memora lists 6 tools with 2 views and 719 GitHub stars.

Can I use both Engram and Memora 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 vs Memora

In-depth architectural comparison of the Engram and Memora 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: 64/100 (Good) | Auth: No auth required

Memora

Knowledge & Memory · Local stdio

Quality: 56/100 (Good) | Auth: API Key required

Verdict Summary: Choose Engram if you need specialized Knowledge & Memory tools running via a local process. Choose Memora 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 Memora 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: MEMORA_DB_PATH, MEMORA_STORAGE_URI, CLOUDFLARE_API_TOKEN, AWS_PROFILE, AWS_ENDPOINT_URL, MEMORA_CLOUD_ENCRYPT, MEMORA_ALLOW_ANY_TAG, MEMORA_GRAPH_PORT.
Primary tools included: Persistent storage with SQLite or cloud sync (S3, R2, D1), Hierarchical memory organization with sections and subsections, Semantic search using TF-IDF, sentence-transformers, and OpenAI embeddings.

Feature & Specification Comparison

Specification	Engram HBarefoot Knowledge & Memory	Memora agentic-mcp-tools 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	Persistent memory with knowledge graph visualization, semantic/hybrid search, cloud sync (S3/R2), and cross-session context management.
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",
        "package"
      ]
    }
  }
}

Memora Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "agentic-mcp-tools-memora": {
      "command": "npx",
      "args": [
        "-y",
        "wrangler"
      ],
      "env": {
        "MEMORA_DB_PATH": "YOUR_MEMORA_DB_PATH_HERE",
        "MEMORA_STORAGE_URI": "YOUR_MEMORA_STORAGE_URI_HERE",
        "CLOUDFLARE_API_TOKEN": "YOUR_CLOUDFLARE_API_TOKEN_HERE",
        "AWS_PROFILE": "YOUR_AWS_PROFILE_HERE",
        "AWS_ENDPOINT_URL": "YOUR_AWS_ENDPOINT_URL_HERE",
        "MEMORA_CLOUD_ENCRYPT": "YOUR_MEMORA_CLOUD_ENCRYPT_HERE",
        "MEMORA_ALLOW_ANY_TAG": "YOUR_MEMORA_ALLOW_ANY_TAG_HERE",
        "MEMORA_GRAPH_PORT": "YOUR_MEMORA_GRAPH_PORT_HERE"
      }
    }
  }
}

Frequently Asked Questions

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

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