Side-by-Side Model Context Protocol Comparison

Engram vs Agentram Mcp

In-depth architectural comparison of the Engram and Agentram Mcp 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: 59/100 (Good) | Auth: No auth required
Agentram Mcp
Knowledge & Memory · Local stdio
Quality: 51/100 (Good) | Auth: No auth required
Verdict Summary: Choose Engram if you need specialized Knowledge & Memory tools running via a local process. Choose Agentram Mcp 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?

Engram logo

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.
Agentram Mcp logo

Choose Agentram Mcp 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: Personal memory storage with agent ID and key, Shared namespaces for multi-agent memory collaboration, Text-based search across keys and values without embeddings.

Feature & Specification Comparison

Specification
Engram logo
Engram
HBarefoot
Knowledge & Memory
Agentram Mcp logo
Agentram Mcp
seanmarkwei
Knowledge & Memory
SummaryLocal-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/engramPersistent memory for AI agents through a simple key-value HTTP API. No vector database or embeddings required. Store, retrieve, search, and share memory across agents with shared namespaces and TTL support. npx -y agentram-mcp
Category & ScopeKnowledge & MemoryKnowledge & Memory
Quality signal59/100 (Good)51/100 (Good)
Transport ProtocolLocal Subprocess (stdio)Local Subprocess (stdio)
Auth RequirementNo auth requiredNo auth required
Pricing ModelFree / Open SourceFree / Open Source
Required Env VarsNone requiredNone required
Compatible Clients
Claude DesktopCursorWindsurfClineVS Code
Claude DesktopCursorWindsurfClineVS Code
Install path signalnpx · highnpx · high
Engagement & Health 1 views 0 copies 0 upvotes 7 stars 0 views 0 copies 0 upvotes 0 stars
Verified / OfficialCommunity ListingCommunity Listing
Open full listingView Engram ListingView Agentram Mcp Listing

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
Health check: memory count, model status, configuration.

Agentram Mcp Tools (6)

Personal memory storage with agent ID and key
Shared namespaces for multi-agent memory collaboration
Text-based search across keys and values without embeddings
TTL support for automatic memory expiry
HTTP API with 10 MCP tools mapping to AgentRAM REST endpoints
Integration instructions for Claude Desktop, Cline, and Cursor clients

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"
      ]
    }
  }
}
Agentram Mcp Configuration
mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "seanmarkwei-agentram-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/inspector"
      ]
    }
  }
}

Frequently Asked Questions

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

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