What is the key difference between Engram and Shodh Memory?

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

How do I install Engram or Shodh 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 and Shodh Memory free or paid?

Engram operates under a Free / Open Source model (No auth required). Shodh Memory operates under a Free / Open Source model (API Key required).

Which MCP server has more tools and community activity?

Engram lists 6 tools with 1 views and 7 GitHub stars. Shodh Memory lists 6 tools with 1 views and 244 GitHub stars.

Can I use both Engram and Shodh 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.

How do I install Engram or Shodh Memory 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 Shodh Memory free to use, or do they require API keys?

Engram is listed under a Free / Open Source model with No auth required . Shodh Memory operates under a Free / Open Source model with API Key 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 Shodh Memory at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both hbarefoot-engram and varun29ankus-shodh-memory 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 59 /100 ( Good ) with 1 views, 0 installs, and 7 GitHub stars. Shodh Memory holds a Quality Score of 55 /100 ( Good ) with 1 views, 0 installs, and 244 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Engram vs Shodh Memory

In-depth architectural comparison of the Engram and Shodh 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

Knowledge & Memory · Local stdio

Quality: 59/100 (Good) | Auth: No auth required

Shodh Memory

Knowledge & Memory · Local stdio

Quality: 55/100 (Good) | Auth: API Key required

Verdict Summary: Choose Engram if you need specialized Knowledge & Memory tools running via a local process. Choose Shodh 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 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 Shodh Memory when:

You need dedicated capabilities in the Knowledge & Memory domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: API Key required (Free / Open Source).
You have access to required keys: SHODH_API_KEY, SHODH_CONFIG_PATH, SHODH_DATA_DIR.
Primary tools included: Zero LLM calls for storing or recalling memories, Hebbian learning with memory strengthening and decay, Local semantic search using MiniLM embeddings.

Explore Shodh Memory Details

Feature & Specification Comparison

Specification	Engram HBarefoot Knowledge & Memory	Shodh Memory varun29ankuS 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	Cognitive memory for AI agents with Hebbian learning, 3-tier architecture, and knowledge graphs. Single 15MB binary, runs offline on edge devices.
Category & Scope	Knowledge & Memory	Knowledge & Memory
Quality signal	59/100 (Good)	55/100 (Good)
Transport Protocol	Local Subprocess (stdio)	Local Subprocess (stdio)
Auth Requirement	No auth required	API Key required
Pricing Model	Free / Open Source	Free / Open Source
Required Env Vars	None required	`SHODH_API_KEYSHODH_CONFIG_PATHSHODH_DATA_DIR`
Compatible Clients	Claude DesktopCursorWindsurfClineVS Code	Claude DesktopCursorWindsurfClineVS Code
Install path signal	`npx · high`	`npx · high`
Engagement & Health	1 views 0 copies 0 upvotes 7 stars	1 views 0 copies 0 upvotes 244 stars
Verified / Official	Community Listing	Community Listing
Open full listing	View Engram Listing	View Shodh Memory 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.

Shodh Memory Tools (6)

Zero LLM calls for storing or recalling memories

Hebbian learning with memory strengthening and decay

Local semantic search using MiniLM embeddings

Named entity recognition and typed relation extraction

Causal lineage tracing via knowledge graph edges

Runs fully offline as a single ~17MB binary

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"
      ]
    }
  }
}

Shodh Memory Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "varun29ankus-shodh-memory": {
      "command": "npx",
      "args": [
        "-y",
        "@shodh/memory-mcp"
      ],
      "env": {
        "SHODH_API_KEY": "YOUR_SHODH_API_KEY_HERE",
        "SHODH_CONFIG_PATH": "YOUR_SHODH_CONFIG_PATH_HERE",
        "SHODH_DATA_DIR": "YOUR_SHODH_DATA_DIR_HERE"
      }
    }
  }
}

Frequently Asked Questions

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

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