Track AI agent costs, detect waste, optimize models, and prove ROI. 23 MCP tools across 10 domains.
The Metrx MCP server (io.github.metrxbots/mcp-server) provides an MCP interface for tracking AI agent costs, detecting waste, optimizing models, and proving ROI. It includes 23 MCP tools across 10 domains, with repository metadata such as an MIT license and CI status badges.
๐ ๏ธ Key Features
Tracks AI agent costs
Detects waste
Optimizes models
Proves ROI
23 MCP tools across 10 domains
๐ Use Cases
Cost tracking for AI agents
Waste detection in AI usage
Model optimization workflows
ROI validation for AI programs
โก Developer Benefits
MCP tool surface area: 23 tools
Coverage across 10 domains
Built as an open-source MIT-licensed server
โ ๏ธ Limitations
Tool capabilities and exact domain list are not included in the provided excerpt
Your AI agents are wasting money. Metrx finds out how much, and fixes it.
The official MCP server for Metrx โ 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.
POST https://metrxbot.com/api/mcp
Authorization: Bearer sk_live_your_key_here
Content-Type: application/json
From npm
bash
npm install @metrxbot/mcp-server
23 Tools Across 10 Domains
Dashboard (3 tools)
Tool
Description
metrx_get_cost_summary
Comprehensive cost summary โ total spend, call counts, error rates, and optimization opportunities
metrx_list_agents
List all agents with status, category, cost metrics, and health indicators
metrx_get_agent_detail
Detailed agent info including model, framework, cost breakdown, and performance history
Optimization (4 tools)
Tool
Description
metrx_get_optimization_recommendations
AI-powered cost optimization recommendations per agent or fleet-wide
metrx_apply_optimization
One-click apply an optimization recommendation to an agent
metrx_route_model
Model routing recommendation for a specific task based on complexity
metrx_compare_models
Compare LLM model pricing and capabilities across providers
Budgets (3 tools)
Tool
Description
metrx_get_budget_status
Current status of all budget configurations with spend vs. limits
metrx_set_budget
Create or update a budget with hard, soft, or monitor enforcement
metrx_update_budget_mode
Change enforcement mode of an existing budget or pause/resume it
Alerts (3 tools)
Tool
Description
metrx_get_alerts
Active alerts and notifications for your agent fleet
metrx_acknowledge_alert
Mark one or more alerts as read/acknowledged
metrx_get_failure_predictions
Predictive failure analysis โ identify agents likely to fail before it happens
Experiments (3 tools)
Tool
Description
metrx_create_model_experiment
Start an A/B test comparing two LLM models with traffic splitting
metrx_get_experiment_results
Statistical significance, cost delta, and recommended action
metrx_stop_experiment
Stop a running model routing experiment and lock in the winner
Cost Leak Detector (1 tool)
Tool
Description
metrx_run_cost_leak_scan
Comprehensive 7-check cost leak audit across your entire agent fleet
Attribution (3 tools)
Tool
Description
metrx_attribute_task
Link agent actions to business outcomes for ROI tracking
metrx_get_task_roi
Calculate return on investment for an agent โ costs vs. attributed outcomes
metrx_get_attribution_report
Multi-source attribution report with confidence scores and top contributors
Alert Configuration (1 tool)
Tool
Description
metrx_configure_alert_threshold
Set cost or operational alert thresholds with email, webhook, or auto-pause
ROI Audit (1 tool)
Tool
Description
metrx_generate_roi_audit
Board-ready ROI audit report for your AI agent fleet
Upgrade Justification (1 tool)
Tool
Description
metrx_get_upgrade_justification
ROI report for tier upgrades based on current usage patterns
Prompts
Pre-built prompt templates for common workflows:
Prompt
Description
analyze-costs
Comprehensive cost overview โ spend breakdown, top agents, optimization opportunities
find-savings
Discover optimization opportunities โ model downgrades, caching, routing
cost-leak-scan
Scan for waste patterns โ retry storms, oversized contexts, model mismatch
Examples
"How much am I spending?"
code
User: What was my AI cost this week?
โ metrx_get_cost_summary(period_days=7)
Total Spend: $234.56 | Calls: 2,450 | Error Rate: 0.2%
โโโ customer-support: $156.23 (1,800 calls)
โโโ code-generator: $78.33 (650 calls)
๐ก Switch customer-support from GPT-4 to Claude Sonnet: Save $42/week
"Find me savings"
code
User: Am I overpaying for my agents?
โ metrx_compare_models(models=["gpt-4o", "claude-3-5-sonnet", "gemini-1.5-pro"])
Model Comparison (per 1M tokens):
โโโ gpt-4o: $2.50 in / $10.00 out
โโโ claude-3-5-sonnet: $3.00 in / $15.00 out
โโโ gemini-1.5-pro: $3.50 in / $10.50 out
"Test a cheaper model"
code
User: Test Claude 3.5 Sonnet against my GPT-4 setup
โ metrx_create_model_experiment(agent_id="agent_123",
model_a="gpt-4o", model_b="claude-3-5-sonnet-20241022", traffic_split=10)
Experiment started: 90% GPT-4o, 10% Claude 3.5 Sonnet
Check back in 14 days for statistical significance.
Companion Tool: Cost Leak Detector
This repo also includes @metrxbot/cost-leak-detector โ a free, offline CLI that scans your LLM API logs for wasted spend. No signup, no cloud, no data leaves your machine.
bash
npx @metrxbot/cost-leak-detector demo
It runs 7 checks (idle agents, premium model overuse, missing caching, high error rates, context overflow, no budgets, arbitrage opportunities) and gives you a scored report in seconds. See the full docs.
Configuration
API Key (required)
The server looks for your API key in this order:
METRX_API_KEY environment variable
~/.metrxrc file (created by --auth)
Run npx @metrxbot/mcp-server --auth to save your key, or set the env var directly.
The product is Metrx (metrxbot.com). The npm scope is @metrxbot and the Smithery listing is metrxbot/mcp-server. The GitHub organization is metrxbots (with an s) because metrxbot was already taken on GitHub. If you see metrxbot vs metrxbots across platforms, they're the same project โ just a GitHub namespace constraint.