What is the key difference between AgentPlaybooks and Elefante?

AgentPlaybooks belongs to the Knowledge & Memory category with local stdio execution, while Elefante belongs to the Knowledge & Memory category with local stdio execution.

How do I install AgentPlaybooks or Elefante 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 AgentPlaybooks and Elefante free or paid?

AgentPlaybooks operates under a Free / Open Source model (No auth required). Elefante operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

AgentPlaybooks lists 0 tools with 0 views and 4 GitHub stars. Elefante lists 0 tools with 0 views and 0 GitHub stars.

Can I use both AgentPlaybooks and Elefante 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 AgentPlaybooks or Elefante 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 AgentPlaybooks and Elefante free to use, or do they require API keys?

AgentPlaybooks is listed under a Free / Open Source model with No auth required . Elefante operates under a Free / Open Source model with No auth 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 AgentPlaybooks and Elefante at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both agentplaybooks and elefante 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, AgentPlaybooks has a Quality Score of 37 /100 ( Fair ) with 0 views, 0 installs, and 4 GitHub stars. Elefante holds a Quality Score of 27 /100 ( Emerging ) with 0 views, 0 installs, and 0 GitHub stars.

Side-by-Side Model Context Protocol Comparison

AgentPlaybooks vs Elefante

In-depth architectural comparison of the AgentPlaybooks and Elefante 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

AgentPlaybooks

Knowledge & Memory · Local stdio

Quality: 37/100 (Fair) | Auth: No auth required

Elefante

Knowledge & Memory · Local stdio

Quality: 27/100 (Emerging) | Auth: No auth required

Verdict Summary: Choose AgentPlaybooks if you need specialized Knowledge & Memory tools running via a local process. Choose Elefante 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 AgentPlaybooks 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).

Explore AgentPlaybooks Details

Choose Elefante 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).

Explore Elefante Details

Feature & Specification Comparison

Specification	AgentPlaybooks Knowledge & Memory	E Elefante Knowledge & Memory
Summary	Portable, vendor-neutral home for agent skills, MCP servers, personas, and memory.	Open, Git-native memory protocol for MCP agents. Portable, versioned, human-editable.
Category & Scope	Knowledge & Memory	Knowledge & Memory
Quality signal

Tools & Capabilities Breakdown

AgentPlaybooks Tools (0)

No explicit tool names declared in metadata yet. Check project README on main listing page.

Elefante Tools (0)

No explicit tool names declared in metadata yet. Check project README on main listing page.

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).

AgentPlaybooks Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "agentplaybooks": {
      "command": "npx",
      "args": [
        "-y",
        "wrangler"
      ]
    }
  }
}

Elefante Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "elefante": {
      "command": "npx",
      "args": [
        "-y",
        "elefante"
      ]
    }
  }
}

Frequently Asked Questions

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

More alternatives to AgentPlaybooks More alternatives to Elefante Knowledge & Memory category hub