What is the key difference between Memory Os Cli and Recallnest?

Memory Os Cli belongs to the Knowledge & Memory category with local stdio execution, while Recallnest belongs to the Knowledge & Memory category with local stdio execution.

How do I install Memory Os Cli or Recallnest 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 Memory Os Cli and Recallnest free or paid?

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

Which MCP server has more tools and community activity?

Memory Os Cli lists 6 tools with 2 views and 12 GitHub stars. Recallnest lists 6 tools with 1 views and 15 GitHub stars.

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

Memory Os Cli is listed under a Free / Open Source model with other . Recallnest 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 Memory Os Cli and Recallnest at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both yonro-memory-os-cli and aliceljy-recallnest 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, Memory Os Cli has a Quality Score of 55 /100 ( Good ) with 2 views, 0 installs, and 12 GitHub stars. Recallnest holds a Quality Score of 59 /100 ( Good ) with 1 views, 0 installs, and 15 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Memory Os Cli vs Recallnest

In-depth architectural comparison of the Memory Os Cli and Recallnest 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

Memory Os Cli

Knowledge & Memory · Local stdio

Quality: 55/100 (Good) | Auth: other

Recallnest

Knowledge & Memory · Local stdio

Quality: 59/100 (Good) | Auth: API Key required

Verdict Summary: Choose Memory Os Cli if you need specialized Knowledge & Memory tools running via a local process. Choose Recallnest 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 Memory Os Cli when:

You need dedicated capabilities in the Knowledge & Memory domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: other (Free / Open Source).
Primary tools included: Hosted Streamable HTTP MCP endpoint, Local stdio MCP command, Authentication and credential management.

Explore Memory Os Cli Details

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.

Feature & Specification Comparison

Specification	Memory Os Cli yonro Knowledge & Memory	Recallnest AliceLJY Knowledge & Memory
Summary	XMemo is user-owned memory for AI agents over a hosted Streamable HTTP MCP endpoint. Save, search, recall, and manage scoped memories across Copilot, Claude, ChatGPT, IDEs, and CLIs. https://xmemo.dev/mcp	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.
Category & Scope

Tools & Capabilities Breakdown

Memory Os Cli Tools (6)

Hosted Streamable HTTP MCP endpoint

Local stdio MCP command

Authentication and credential management

Client setup and configuration generation

Diagnostics and smoke checks

Behavior profiles and native integrations for selected clients

Recallnest 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).

Memory Os Cli Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "yonro-memory-os-cli": {
      "command": "npx",
      "args": [
        "-y",
        "--package",
        "@xmemo/client@latest",
        "xmemo-mcp"
      ]
    }
  }
}

Recallnest Configuration

mcpServers (Claude Desktop / Cursor)

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

Frequently Asked Questions

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

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