FairMind Project Context vs Kawa Code

In-depth architectural comparison of the FairMind Project Context and Kawa Code 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?

F

Choose FairMind Project Context when:

• You need dedicated capabilities in the Knowledge & Memory domain.
• You prefer remote streaming HTTP/SSE transport architecture.
• Your security boundary fits: No auth required (Free / Open Source).

Explore FairMind Project Context Details

Choose Kawa Code 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 Kawa Code Details

Feature & Specification Comparison

Specification	F FairMind Project Context Knowledge & Memory	Kawa Code Knowledge & Memory
Summary	Project memory for coding agents: requirements, decisions, code graph and delivery telemetry.	Team-aware memory: intent, decisions, real-time conflicts for AI coding assistants.
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": {
    "fairmind-project-context": {
      "url": "https://fairmind.ai"
    }
  }
}

{
  "mcpServers": {
    "kawa-code": {
      "command": "npx",
      "args": [
        "-y",
        "@kawacode/mcp"
      ]
    }
  }
}

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