Llm Latency Tracker vs Mcp Server

In-depth architectural comparison of the Llm Latency Tracker and Mcp Server 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?

L

Choose Llm Latency Tracker when:

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

Explore Llm Latency Tracker Details

Choose Mcp Server when:

• You need dedicated capabilities in the Monitoring domain.
• You prefer local stdio subprocess transport architecture.
• Your security boundary fits: No auth required (Free / Open Source).
• Primary tools included: log_trace, evaluate_output, get_traces.

Explore Mcp Server Details

Feature & Specification Comparison

Specification	L Llm Latency Tracker Monitoring	Mcp Server iris-eval Monitoring
Summary	Measured latency & uptime for AI inference APIs, by region. Exposes a get_ai_api_latency tool.	MCP-native agent evaluation and observability server with trace logging, output quality evaluation, cost tracking, 12 built-in eval rules, real-time dashboard, and PII detection.
Category & Scope	Monitoring	Monitoring

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": {
    "llm-latency-tracker": {
      "command": "npx",
      "args": [
        "-y",
        "llm-latency-tracker"
      ]
    }
  }
}

{
  "mcpServers": {
    "iris-eval-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@iris-eval/mcp-server"
      ]
    }
  }
}

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