Face Recognition MCP Server vs TokenSave

In-depth architectural comparison of the Face Recognition MCP Server and TokenSave 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 Face Recognition MCP Server when:

• You need dedicated capabilities in the Developer Tools domain.
• You prefer local stdio subprocess transport architecture.
• Your security boundary fits: No auth required (Free / Open Source).
• Primary tools included: detect_faces, check_liveness, assess_quality.

Explore Face Recognition MCP Server Details

Choose TokenSave when:

• You need dedicated capabilities in the Developer Tools domain.
• You prefer local stdio subprocess transport architecture.
• Your security boundary fits: No auth required (Free / Open Source).

Explore TokenSave Details

Feature & Specification Comparison

Specification	F Face Recognition MCP Server Developer Tools	TokenSave Developer Tools
Summary	On-premise face recognition MCP server for 3DiVi Face SDK. No cloud required.	Code intelligence for 15+ languages: semantic graph queries instead of file reads. 37 MCP tools.
Category & Scope	Developer Tools	Developer Tools
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": {
    "face-recognition-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "face-recognition-mcp-server"
      ]
    }
  }
}

{
  "mcpServers": {
    "tokensave": {
      "command": "npx",
      "args": [
        "-y",
        "@colbymchenry/codegraph"
      ]
    }
  }
}

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