What is the key difference between Recallnest and Shodh Memory?

Recallnest 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 Recallnest 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 Recallnest and Shodh Memory free or paid?

Recallnest operates under a Free / Open Source model (API Key required). Shodh Memory operates under a Free / Open Source model (API Key required).

Which MCP server has more tools and community activity?

Recallnest lists 6 tools with 1 views and 15 GitHub stars. Shodh Memory lists 6 tools with 1 views and 244 GitHub stars.

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

Recallnest is listed under a Free / Open Source model with API Key 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 Recallnest and Shodh Memory at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both aliceljy-recallnest 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, Recallnest has a Quality Score of 44 /100 ( Fair ) with 1 views, 0 installs, and 15 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

Recallnest vs Shodh Memory

In-depth architectural comparison of the Recallnest 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

Recallnest

Knowledge & Memory · Local stdio

Quality: 44/100 (Fair) | Auth: API Key required

Shodh Memory

Knowledge & Memory · Local stdio

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

Verdict Summary: Choose Recallnest 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 Recallnest 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: JINA_API_KEY.
Primary tools included: Hybrid retrieval: vector, BM25, multi-vector levels, and knowledge graph PPR, Session checkpoint and resume with repo-state guarding, Multi-scope isolation with related scope sidecar search.

Explore Recallnest 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.

Feature & Specification Comparison

Specification	Recallnest AliceLJY Knowledge & Memory	Shodh Memory varun29ankuS Knowledge & Memory
Summary	Persistent memory MCP server for AI coding agents (Claude Code, Codex, Gemini CLI). Hybrid retrieval (vector + BM25), cross-encoder reranking, knowledge graph with PPR traversal, session checkpoint/resume, and multi-scope isolation. Local-first with LanceDB + SQLite, zero external dependencies.	Cognitive memory for AI agents with Hebbian learning, 3-tier architecture, and knowledge graphs. Single 15MB binary, runs offline on edge devices.
Category & Scope

Tools & Capabilities Breakdown

Recallnest Tools (6)

Hybrid retrieval: vector, BM25, multi-vector levels, and knowledge graph PPR

Session checkpoint and resume with repo-state guarding

Multi-scope isolation with related scope sidecar search

Memory lifecycle management: decay, consolidation, promotion, and archival

Privacy tiers with cascade forgetting and write-time admission control

Dual interface: MCP stdio for CLI and HTTP API for custom clients

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).

Recallnest Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "aliceljy-recallnest": {
      "command": "npx",
      "args": [
        "-y",
        "aliceljy-recallnest"
      ],
      "env": {
        "JINA_API_KEY": "YOUR_JINA_API_KEY_HERE"
      }
    }
  }
}

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

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

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