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Servers/Monitoring/iris-eval/mcp-server
MonitoringOfficialTypeScript
I

iris-eval/mcp-server

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.

0 starsUpdated Aug 28, 2026
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Overview

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.

Installation

npx @iris-eval/mcp-server --demo

Configuration

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

Capabilities

  • Log agent runs

    Ask to record an execution with `log_trace`, including spans, tool calls, token usage, and cost in USD.

  • Score output quality

    Use `evaluate_output` to check completeness, relevance, safety, and cost against 13 built-in rules.

  • Query trace history

    Retrieve stored runs with `get_traces`, filtering by time range, pagination, and other criteria.

  • Manage custom rules

    Deploy new eval rules with `deploy_rule` or remove them via `delete_rule` to tailor scoring.

  • Run LLM-as-judge

    Invoke `evaluate_with_llm_judge` for semantic scoring across five templates, with a hard per-eval cost cap.

  • Verify citations

    Use `verify_citations` to extract and fact-check cited sources against claims via an LLM judge.

Tags

  • development
  • awesome-list

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