Metrx MCP Server

Metrx MCP Server

An MCP server for Metrx — provides tools for construction, healthcare, logistics, manufacturing, and legal mid-market businesses to query and analyze their operational data via AI.

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Metrx MCP Server

<!-- mcp-name: io.github.metrxbots/mcp-server -->

npm version CI License: MIT Smithery

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.

Links

License

MIT — see LICENSE.

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