Dakera MCP vs Garnet MCP

In-depth architectural comparison of the Dakera MCP and Garnet MCP 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?

Choose Dakera MCP 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 Dakera MCP Details

Choose Garnet MCP 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 Garnet MCP Details

Feature & Specification Comparison

Specification	Dakera MCP Knowledge & Memory	Garnet MCP Knowledge & Memory
Summary	Decay-weighted vector memory for AI agents — 83 MCP tools: store, recall, search, knowledge graphs.	RAG memory for LLM agents over Garnet Vector Sets: store text as embeddings, recall by meaning.
Category & Scope	Knowledge & Memory	Knowledge & Memory

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": {
    "dakera-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@dakera-ai/dakera-mcp"
      ]
    }
  }
}

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

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