mcp-agent-monitor

Make your AI agents reliable — one log at a time.

A production-ready MCP (Model Context Protocol) server that analyzes AI agent execution logs, calculates reliability scores, detects failure patterns, and suggests concrete improvements.

Perfect for entrepreneurs and teams building AI agents who want to stop guessing why agents fail and start fixing them with data.

Why this exists

AI agents fail silently. You see a wrong answer but you don't know:

• Which tool call broke?
• Is it a timeout, bad parameter, or cascading error?
• Is the agent getting better or worse over time?

This MCP server turns raw agent traces into clear reliability insights — 100% local computation, zero paid API calls.

Features (Tools)

Tool	What it does
analyze_agent_trace	Full analysis: score + patterns + suggestions
score_reliability	Quick 0-100 reliability score
detect_failure_patterns	Only the failure patterns
compare_traces	Before vs After comparison
generate_reliability_report	Beautiful Markdown report for humans

Quick Start

1. Install

npm install
npm run build

2. Run (stdio)

node dist/index.js

3. Add to your MCP client (Claude Desktop / Cursor / etc.)

{
  "mcpServers": {
    "agent-monitor": {
      "command": "node",
      "args": ["/path/to/mcp-agent-monitor/dist/index.js"]
    }
  }
}

Example Usage

Give the agent a log like this:

{
  "agent_id": "sales-outreach-v2",
  "steps": [
    { "tool": "search_leads", "success": true, "duration_ms": 340 },
    { "tool": "send_email", "success": false, "error": "rate limit exceeded", "duration_ms": 1200 },
    { "tool": "send_email", "success": false, "error": "rate limit exceeded", "duration_ms": 1100 }
  ]
}

Call analyze_agent_trace → get score, pattern ("Repeated failure on tool send_email"), and suggestions.

Project Structure

mcp-agent-monitor/
├── src/
│   └── index.ts          # Full MCP server + all tools
├── tests/
│   └── reliability.test.ts
├── mcpize.yaml           # MCP metadata
├── package.json
├── tsconfig.json
├── .env.example
├── LAUNCH.md
└── README.md

Pricing Suggestion (for marketplace)

• Free tier: 50 analyses / month
• Pro: $19/mo unlimited + team sharing
• Enterprise: custom (SSO, private deployment)

Author

Built by Prince Ruhul (@princeruhulofficial)
Founder of Prevalid — Making AI Accountable at infrastructure level.

License

MIT