Runapi AI MCP vs Topaz MCP

In-depth architectural comparison of the Runapi AI MCP and Topaz 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 Runapi AI MCP when:

• You need dedicated capabilities in the Multimedia Process domain.
• You prefer local stdio subprocess transport architecture.
• Your security boundary fits: API Key required (Free / Open Source).
• You have access to required keys: RUNAPI_API_KEY.
• Primary tools included: list_models, get_model_info, list_actions.

Explore Runapi AI MCP Details

Choose Topaz MCP when:

• You need dedicated capabilities in the Multimedia Process domain.
• You prefer local stdio subprocess transport architecture.
• Your security boundary fits: API Key required (BYOK (Pay Provider Direct)).
• You have access to required keys: TOPAZ_API_KEY.
• Primary tools included: image-enhance.

Feature & Specification Comparison

Specification	Runapi AI MCP runapi-ai Multimedia Process	Topaz MCP TopazLabs Multimedia Process
Summary	Unified AI model API for 130+ models across 18 providers. Browse models, check pricing, create image/video/music/audio tasks, poll results, check balance, and call LLM endpoints. Free catalog tools work without an API key. npx @runapi.ai/mcp	AI image enhancement (upscaling, denoising, sharpening) via Topaz Labs API. Supports 8 models including Standard V2, Wonder 2, Bloom, and Recover 3.
Category & Scope

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": {
    "runapi-ai-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@runapi.ai/mcp"
      ],
      "env": {
        "RUNAPI_API_KEY": "YOUR_RUNAPI_API_KEY_HERE"
      }
    }
  }
}

{
  "mcpServers": {
    "topazlabs-topaz-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@topazlabs/mcp"
      ],
      "env": {
        "TOPAZ_API_KEY": "YOUR_TOPAZ_API_KEY_HERE"
      }
    }
  }
}

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