What is the key difference between Entroly and Shodh Memory?

Entroly 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 Entroly 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 Entroly and Shodh Memory free or paid?

Entroly 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?

Entroly lists 6 tools with 1 views and 435 GitHub stars. Shodh Memory lists 6 tools with 1 views and 244 GitHub stars.

Can I use both Entroly 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 Entroly 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 Entroly and Shodh Memory free to use, or do they require API keys?

Entroly 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 Entroly and Shodh Memory at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both juyterman1000-entroly 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, Entroly has a Quality Score of 55 /100 ( Good ) with 1 views, 0 installs, and 435 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

Entroly vs Shodh Memory

In-depth architectural comparison of the Entroly 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

Entroly

Knowledge & Memory · Local stdio

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

Shodh Memory

Knowledge & Memory · Local stdio

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

Verdict Summary: Choose Entroly 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 Entroly 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: Recoverable compression using BM25, entropy, and dependency graph knapsack, Stable prompt prefixing for provider cache discounts, Bayesian routing of tasks to cheaper models.

Explore Entroly 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.

Feature & Specification Comparison

Specification	Entroly juyterman1000 Knowledge & Memory	Shodh Memory varun29ankuS Knowledge & Memory
Summary	Auditable context control plane and MCP server for AI coding agents. Compresses context 70–95% (BM25 + entropy + dep-graph knapsack), stabilizes prompt prefixes for provider cache discounts, routes easy tasks to cheaper models (RAVS Bayesian router), and verifies answers locally with WITNESS hallucination guard (0.844 AUROC, $0, 3 ms). MemoryOS adds local budget-aware working/episodic/semantic memory with decay, safety scanning, and durable persistence. 38 agent integrations (Cursor, Claude Code, Codex, Aider, and more). Ships as MCP server (entroly serve), HTTP proxy, or Python/Rust library. Apache-2.0, local-first. pip install entroly	Cognitive memory for AI agents with Hebbian learning, 3-tier architecture, and knowledge graphs. Single 15MB binary, runs offline on edge devices.

Tools & Capabilities Breakdown

Entroly Tools (6)

Recoverable compression using BM25, entropy, and dependency graph knapsack

Stable prompt prefixing for provider cache discounts

Bayesian routing of tasks to cheaper models

Local hallucination guard with WITNESS (0.844 AUROC)

MemoryOS with working, episodic, and semantic memory plus decay and persistence

Auditable receipts documenting context selection decisions

Shodh Memory Tools (6)

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).

Entroly Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "juyterman1000-entroly": {
      "command": "uvx",
      "args": [
        "entroly"
      ]
    }
  }
}

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

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

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