Iris Eval
📇 ☁️ 🏠 🍎 🪟 🐧 - MCP-native agent evaluation and observability server with trace logging, output
What is Iris Eval?
Iris Eval is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to 📇 ☁️ 🏠 🍎 🪟 🐧 - mcp-native agent evaluation and observability server with trace logging, output
📇 ☁️ 🏠 🍎 🪟 🐧 - MCP-native agent evaluation and observability server with trace logging, output
This server falls under the Monitoring & Observability category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- MCP protocol support
Use Cases
Maintainer
Works with
Installation
NPM
npx -y @iris-eval/mcp-serverManual Installation
npx -y @iris-eval/mcp-serverConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
Frequently Asked Questions about Iris Eval
What is Iris Eval?
Iris Eval is a Model Context Protocol (MCP) server that 📇 ☁️ 🏠 🍎 🪟 🐧 - mcp-native agent evaluation and observability server with trace logging, output It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Iris Eval?
Install via npm with the command: npx -y @iris-eval/mcp-server. Then add the server configuration to your AI client's JSON config file (e.g., claude_desktop_config.json or .cursor/mcp.json).
Which AI clients work with Iris Eval?
Iris Eval works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Iris Eval free to use?
Yes, Iris Eval is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.
Iris Eval Alternatives — Similar Monitoring & Observability Servers
Looking for alternatives to Iris Eval? Here are other popular monitoring & observability servers you can use with Claude, Cursor, and VS Code.
Netdata
★ 78.9kReal-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Kubeshark
★ 11.9keBPF-powered network observability for Kubernetes. Indexes L4/L7 traffic with full K8s context, decrypts TLS without keys. Queryable by AI agents via MCP and humans via dashboard.
Mission Control
★ 4.9kSelf-hosted AI agent orchestration platform: dispatch tasks, run multi-agent workflows, monitor spend, and govern operations from one mission control dashboard.
Grafana
★ 3.0kThis MCP server enables natural-language querying of Grafana logs by automatically detecting log sources and service labels. It provides read-only access to log data with intelligent caching for efficient repeat queries.
Sentrux
★ 2.4kReal-time architectural sensor that helps AI agents close the feedback loop, enabling recursive self-improvement of code quality. Pure Rust.
OpenInference
★ 986OpenTelemetry Instrumentation for AI Observability
Browse More Monitoring & Observability MCP Servers
Explore all monitoring & observability servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.
Set Up Iris Eval in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
Ready to use Iris Eval?
Browse our complete directory of 33,000+ MCP servers, read setup guides for your editor, and start building with the Model Context Protocol.