Iris — MCP-Native Agent Eval & Observability

See what your AI agents are actually doing. Iris is an open-source MCP server that logs every trace, evaluates output quality, and tracks costs across all your agents. Any MCP-compatible agent discovers and uses it automatically — no SDK, no code changes.

The Problem

Your agents are running in production. Traditional monitoring sees 200 OK and moves on. It has no idea the agent just:

• Leaked a social security number in its response
• Hallucinated an answer with zero factual grounding
• Burned $0.47 on a single query — 4.7x your budget threshold
• Made 6 tool calls when 2 would have sufficed

Iris sees all of it.

What You Get

Quickstart

Add Iris to your Claude Desktop (or Cursor, Claude Code, Windsurf) MCP config:

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

That's it. Your agent discovers Iris and starts logging traces automatically.

Want the dashboard?

npx @iris-eval/mcp-server --dashboard
# Open http://localhost:6920

Other Install Methods

# Global install
npm install -g @iris-eval/mcp-server
iris-mcp --dashboard

# Docker
docker run -p 3000:3000 -v iris-data:/data ghcr.io/iris-eval/mcp-server

MCP Tools

Iris registers three tools that any MCP-compatible agent can invoke:

• log_trace — Log an agent execution with spans, tool calls, token usage, and cost
• evaluate_output — Score output quality against completeness, relevance, safety, and cost rules
• get_traces — Query stored traces with filtering, pagination, and time-range support

Full tool schemas and configuration: iris-eval.com

Cloud Tier (Coming Soon)

Self-hosted Iris runs on your machine with SQLite. As your team grows, the cloud tier adds PostgreSQL, team dashboards, alerting, and managed infrastructure.

Join the waitlist to get early access.

Examples

• Claude Desktop setup — MCP config for stdio and HTTP modes
• TypeScript — MCP SDK client usage
• LangChain — Agent instrumentation
• CrewAI — Crew observability

Community

• GitHub Issues — Bug reports and feature requests
• GitHub Discussions — Questions and ideas
• Contributing Guide — How to contribute
• Roadmap — What's coming next

# Production deployment
iris-mcp --transport http --port 3000 --api-key "$(openssl rand -hex 32)" --dashboard

If Iris is useful to you, consider starring the repo — it helps others find it.

MIT Licensed.