Metrx MCP Server

MCPOfficialOpen SourceMIT28.5

by metrxbots • Uncategorized

An MCP server that tracks AI agent costs, detects waste, optimizes model selection, and proves ROI.

Example Use Cases

1
Real-time cost tracking and spend visibility
2
AI-powered cost optimization and budget enforcement
3
Prove ROI and link agent actions to business outcomes

Description

Metrx MCP Server provides real-time cost intelligence for AI agents by monitoring spend, detecting cost leaks, enforcing budgets, and recommending optimizations. It supports multiple MCP-compatible agents and offers a suite of 23 tools across 10 domains including dashboards, optimization, budgets, alerts, experiments, and ROI audits. This helps organizations reduce wasted spend, improve cost efficiency, and demonstrate AI ROI effectively.

Capabilities(26 total)

Tools (23)

metrx_get_cost_summary

Get a comprehensive cost summary for your AI agent fleet. Returns total spend, call counts, error rates, agent breakdown, revenue attribution (if available), and optimization opportunities. Use this as the starting point for understanding your agent economics. Do NOT use for real-time per-request cost checking — use OpenTelemetry spans for that.

period_days:integer

metrx_list_agents

List all AI agents in your organization with their status, category, and cost. Optionally filter by status or category. Returns agent IDs needed for other tools. Do NOT use for detailed per-agent analysis — use get_agent_detail for that.

status:stringcategory:string

metrx_get_agent_detail

Get detailed information about a specific agent including its model, framework, category, outcome configuration, and failure risk score. Do NOT use for fleet-wide overviews — use get_cost_summary instead.

agent_id:string*

metrx_get_optimization_recommendations

Get AI-powered cost optimization recommendations for a specific agent or your entire fleet. Returns actionable suggestions including model switching, token guardrails, provider arbitrage, batch processing opportunities, and revenue intelligence insights. Each suggestion includes estimated monthly savings and confidence level. Do NOT use for implementing fixes — use apply_optimization for one-click fixes or create_model_experiment to validate first.

agent_id:stringinclude_revenue:boolean

metrx_apply_optimization

Apply a one-click optimization recommendation to an agent. Only works for suggestions marked as "one_click: true". Common optimizations include setting max_tokens limits and switching models. Do NOT use for unvalidated changes — run create_model_experiment first if unsure about impact.

agent_id:string*optimization_type:string*payload:object

Prompts (3)

analyze-costs

Get a comprehensive overview of your AI agent costs including spend breakdown, top-spending agents, error rates, and optimization opportunities.

period_days

find-savings

Discover optimization opportunities across your AI agent fleet. Identifies model downgrades, caching opportunities, and routing improvements.

cost-leak-scan

Scan for waste patterns in your AI agent operations — retry storms, oversized contexts, model mismatch, and missing caching.

agent_id

Quick Actions

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Security

Scanned 1 month(s) ago

Risk Level

MINIMAL

Read-only data retrieval, no side effects

Trust Score

B70/100

13/17 checks passed

Scores are informational only and provided “as is” without warranty. AgentHotspot assumes no liability for actions taken based on these ratings.

Quick Stats

Service TypeMCP

Pricing ModelFreemium

Capabilities23 Tools / 3 Prompts / 0 Resources

Ownermetrxbots

CategoryUncategorized

DependenciesStandalone

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