Iris Eval MCP Server

What the code does

We read the source, 20 h ago · rules 3dff92dd89df

What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.

    const child = spawn(command, args, {

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

claude mcp add mcp-server -- npx -y @iris-eval/mcp-server

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

[mcp_servers.mcp-server]
command = "npx"
args = ["-y", "@iris-eval/mcp-server"]

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

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

This one needs environment variables set before it will start: IRIS_API_KEY (API key for HTTP authentication. Required to bind the HTTP transport or the dashboard beyond loopback (0.0.0.0, a LAN address, a container): without it the server refuses to start), IRIS_ALLOW_UNAUTHENTICATED (Set to 1 to run a non-loopback bind with NO API key on purpose (lifts the startup refusal; the network is then your boundary)), IRIS_DB_PATH (SQLite database path), IRIS_LOG_LEVEL (Log level: debug, info, warn, error), IRIS_HOME (Directory for the database, custom rules and preferences (default ~/.iris)), IRIS_ANTHROPIC_API_KEY (Enables evaluate_with_llm_judge and verify_citations with an Anthropic model. Optional: the deterministic rules never need a key), IRIS_OPENAI_API_KEY (Enables evaluate_with_llm_judge and verify_citations with an OpenAI model. Optional: the deterministic rules never need a key), IRIS_LLM_JUDGE_MAX_COST_USD_PER_EVAL (Hard cap on the worst-case cost of one judge or citation call (default 0.25)), IRIS_CITATION_ALLOW_FETCH (Let verify_citations fetch URLs (off by default)), IRIS_DASHBOARD (Start the dashboard alongside the server (same as --dashboard)), IRIS_DASHBOARD_PORT (Dashboard port (default 6920); IRIS_PORT is the MCP HTTP transport port (default 3000)), IRIS_PORT (MCP HTTP transport port (default 3000); only used with --transport http), IRIS_OTEL_ENDPOINT (OTLP/HTTP collector URL; when set, every stored trace is also exported as OpenTelemetry spans (best-effort, asynchronous)), IRIS_CITATION_DOMAINS (Comma-separated domain allowlist for verify_citations fetches (only consulted when IRIS_CITATION_ALLOW_FETCH is on)), IRIS_TRANSPORT (Transport: stdio (default) or http; same as --transport), IRIS_HOST (Bind host for the HTTP transport (default 127.0.0.1); only used with --transport http), IRIS_ALLOWED_ORIGINS (Comma-separated Origin allowlist for the HTTP transport and dashboard CORS (default http://localhost:*)), IRIS_DASHBOARD_HOST (Bind host for the dashboard (default 127.0.0.1); same as --dashboard-host), IRIS_OTEL_HEADERS (Comma-separated key=value headers sent with every OTLP export (for example an auth token for your collector)), IRIS_OTEL_SERVICE_NAME (service.name resource attribute on exported spans (default iris-eval)), IRIS_OTEL_TIMEOUT_MS (Timeout in milliseconds for each OTLP export request). The author declared them in the registry entry; get the values from the project itself.