Metrx MCP Server

Your AI agents are wasting money. Metrx finds out how much, and fixes it.

The official MCP server for Metrx — the AI Agent Cost Intelligence Platform. Give any MCP-compatible agent (Claude, GPT, Gemini, Cursor, Windsurf) the ability to track its own costs, detect waste, optimize model selection, and prove ROI.

Why Metrx?

Problem	What Metrx Does
No visibility into agent spend	Real-time cost dashboards per agent, model, and provider
Overpaying for LLM calls	Provider arbitrage finds cheaper models for the same task
Runaway costs	Budget enforcement with auto-pause when limits are hit
Wasted tokens	Cost leak scanner detects retry storms, context bloat, model mismatch
Can't prove AI ROI	Revenue attribution links agent actions to business outcomes

Quick Start

One-command install (Claude Desktop, Cursor, Windsurf)

{
  "mcpServers": {
    "metrx": {
      "command": "npx",
      "args": ["@metrxbot/mcp-server"],
      "env": {
        "METRX_API_KEY": "sk_live_your_key_here"
      }
    }
  }
}

Get your free API key at metrxbot.com/settings/security.

Remote HTTP endpoint

For remote agents (no local install needed):

POST https://metrxbot.com/api/mcp
Authorization: Bearer sk_live_your_key_here
Content-Type: application/json

From npm

npm install @metrxbot/mcp-server

23 Tools Across 10 Domains

Dashboard (2 tools)

Tool	Description
`metrx_get_cost_summary`	Total spend, call counts, error rates, agent breakdown, and optimization opportunities
`metrx_list_agents`	All agents with status, category, cost metrics, and health indicators

Optimization (4 tools)

Tool	Description
`metrx_get_provider_arbitrage`	Compare costs across providers — find cheaper alternatives
`metrx_get_revenue_intelligence`	Revenue per agent with confidence scores and ROI metrics
`metrx_get_token_guardrails`	Token limit recommendations and overflow detection
`metrx_get_model_recommendations`	Model switching recommendations based on cost, latency, quality

Budgets (4 tools)

Tool	Description
`metrx_create_budget`	Create monthly/daily budgets with hard, soft, or monitor enforcement
`metrx_update_budget`	Update limits, frequency, or enforcement mode
`metrx_list_budgets`	All budgets with current spend vs. limits
`metrx_delete_budget`	Remove a budget (historical data preserved)

Alerts (3 tools)

Tool	Description
`metrx_create_alert_policy`	Alert on cost overages, error rates, latency spikes, anomalies
`metrx_update_alert_policy`	Update thresholds, channels, enable/disable
`metrx_list_alerts`	Active alerts and current status per agent

Experiments (2 tools)

Tool	Description
`metrx_start_experiment`	A/B test comparing two LLM models with traffic splitting
`metrx_get_experiment_results`	Statistical significance, cost delta, and recommended action

Cost Leak Detector (2 tools)

Tool	Description
`metrx_scan_cost_leaks`	Find cost anomalies and waste across your fleet
`metrx_analyze_cost_leak`	Deep-dive into a specific anomaly with timeline and root cause

Attribution (2 tools)

Tool	Description
`metrx_attribute_task`	Link agent actions to business outcomes for ROI tracking
`metrx_get_attribution_report`	Multi-source attribution report with confidence scores

ROI & Reporting (2 tools)

Tool	Description
`metrx_get_upgrade_justification`	ROI report for tier upgrades based on usage patterns
`metrx_generate_roi_audit`	Board-ready ROI audit report

Alert Configuration (2 tools)

Tool	Description
`metrx_configure_alert_threshold`	Set cost/operational thresholds with email, webhook, or auto-pause
`metrx_get_failure_predictions`	Predictive analysis — identify agents likely to fail before it happens

Prompts

Pre-built prompt templates for common workflows:

Prompt	Description
`analyze-costs`	Comprehensive cost overview — spend breakdown, top agents, optimization opportunities
`find-savings`	Discover optimization opportunities — model downgrades, caching, routing
`cost-leak-scan`	Scan for waste patterns — retry storms, oversized contexts, model mismatch

Examples

"How much am I spending?"

User: What was my AI cost this week?
→ metrx_get_cost_summary(period_days=7)

Total Spend: $234.56 | Calls: 2,450 | Error Rate: 0.2%
├── customer-support: $156.23 (1,800 calls)
└── code-generator: $78.33 (650 calls)

💡 Switch customer-support from GPT-4 to Claude Sonnet: Save $42/week

"Find me savings"

User: Am I overpaying for my agents?
→ metrx_get_provider_arbitrage(agent_id="agent_123")

Current: GPT-4 @ $15.20/1K calls
Alternative: Gemini 1.5 @ $6.80/1K calls (-55%)
Estimated Savings: $420/month

"Test a cheaper model"

User: Test Claude 3.5 Sonnet against my GPT-4 setup
→ metrx_start_experiment(name="Claude Trial", agent_id="agent_123",
    model_a="gpt-4", model_b="claude-3-5-sonnet", traffic_split=10)

Experiment started: 90% GPT-4, 10% Claude 3.5 Sonnet
Check back in 14 days for statistical significance.

Configuration

Variable	Required	Description
`METRX_API_KEY`	Yes	Your Metrx API key (get one free)
`METRX_API_URL`	No	Override API base URL (default: `https://metrxbot.com/api/v1`)

Rate Limiting

60 requests per minute per tool. For higher limits, contact support@metrxbot.com.

Development

git clone https://github.com/metrxbots/mcp-server.git
cd mcp-server
npm install
npm run typecheck
npm test

Contributing

See CONTRIBUTING.md for guidelines.

License

MIT — see LICENSE.

mcp-server

Quick Install