AI Readiness Kit vs RAGScore

In-depth architectural comparison of the AI Readiness Kit and RAGScore 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.

Which MCP Server Should You Choose?

A

Choose AI Readiness Kit 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 AI Readiness Kit Details

Choose RAGScore 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 RAGScore Details

Feature & Specification Comparison

Specification	A AI Readiness Kit Knowledge & Memory	RAGScore Knowledge & Memory
Summary	Generate 18 AI readiness files (llms.txt, ai.txt, RAG indexes, schema) for any website.	Generate QA datasets & evaluate RAG systems. Privacy-first, any LLM, local or cloud.
Category & Scope	Knowledge & Memory	Knowledge & Memory
Quality signal

Tools & Capabilities Breakdown

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).

{
  "mcpServers": {
    "ai-readiness-kit": {
      "command": "npx",
      "args": [
        "-y",
        "@silverbackmarketing/ai-readiness"
      ]
    }
  }
}

{
  "mcpServers": {
    "ragscore": {
      "command": "uvx",
      "args": [
        "ragscore"
      ]
    }
  }
}

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