Metrxbots

io.github.metrxbotsPublished by GitHub account metrxbotsv0.2.2Updated Oct 24, 2026

Track AI agent costs, detect waste, optimize models, and prove ROI. 23 MCP tools across 10 domains.

VerifiedSTDIODesktop onlyFinance Data & Analytics AI & ML

Server details

Identifier: io.github.metrxbots/mcp-server
Transport: STDIO
Runtime: Desktop only
Trust: Verified
Published: Sep 16, 2026

Security note

MCP servers receive tool arguments from a conversation and may perform external actions. Review what a server can do before you enable it, and give it only the access it needs.

The registry verified the GitHub account metrxbots for this listing. That does not show the account is the product's maker.

SourceWeft's checks cover whether the listing is complete and the endpoint answered; they do not review the server's code or what its tools do.

Add a badge to your README

Show readers this MCP server is listed on SourceWeft. The badge links to this page.

[![Listed on SourceWeft](https://sourceweft.com/badge/mcp/io.github.metrxbots%2Fmcp-server.svg)](https://sourceweft.com/mcp/io.github.metrxbots%2Fmcp-server?utm_source=readme&utm_medium=badge)

Overview

AI-generated overview

Metrx is a local MCP server that lets an assistant read AI agent cost data, find waste, compare models, manage budgets and produce ROI reports.

What you can do: Read cost summaries, agent lists and per-agent cost and performance detail, plus active alerts and failure predictions, and acknowledge alerts. Get optimization recommendations, apply them, route tasks to models and compare model pricing. View, create and change budgets, including enforcement modes and pause or resume. Run model A/B experiments, read results and stop experiments. Run a cost leak scan, attribute tasks to business outcomes and pull ROI and attribution reports. Set alert thresholds and generate ROI audit and upgrade justification reports.
When to use it: Useful when you already run AI agents through Metrx and want an assistant to check spend, investigate overpaying or runaway costs, test cheaper models, or assemble ROI and audit reports without opening the dashboard.
Requirements: Runs locally via npx or npm, so Node.js is needed. A Metrx account and API key are required, supplied through the METRX_API_KEY environment variable or saved to a local config file by the interactive login flag; a demo mode runs on sample data without a key. Network access to the Metrx API is required.

Before you install

The API key is a live credential stored in an environment variable or a local config file, so protect it. Several tools change state: applying optimizations, setting or pausing budgets, starting and stopping experiments, acknowledging alerts and configuring alert thresholds with email, webhook or auto-pause. Cost and usage data is sent to the Metrx service.

Installation

In SourceWeft

Open Metrxbots in the dashboard and add it to a workspace.
Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

Metrx MCP Server

[npm version] [CI] [License: MIT] [Smithery] [Glama]

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.

[Metrx Server MCP server]

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

Try it now — no signup required

This starts the server with sample data so you can explore all 23 tools instantly.

Connect your real data

Option A — Interactive login (recommended):

Opens your browser to get an API key, validates it, and saves it to ~/.metrxrc so you never need to set env vars.

Option B — Environment variable:

Get your free API key at app.metrxbot.com/sign-up.

Add to your MCP client (Claude Desktop, Cursor, Windsurf)

If you used --auth, no env block is needed — the key is read from ~/.metrxrc automatically:

json

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

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

Or pass the key explicitly via environment:

json

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

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

Remote HTTP endpoint

For remote agents (no local install needed):

POST https://metrxbot.com/api/mcpAuthorization: Bearer sk_live_your_key_hereContent-Type: application/json

POST https://metrxbot.com/api/mcpAuthorization: Bearer sk_live_your_key_hereContent-Type: application/json

From npm

23 Tools Across 10 Domains

Dashboard (3 tools)

Tool	Description
`metrx_get_cost_summary`	Comprehensive cost summary — 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 — 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)

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 — costs vs. attributed outcomes
`metrx_get_attribution_report`	Multi-source attribution report with confidence scores and top contributors

Alert Configuration (1 tool)

ROI Audit (1 tool)

Upgrade Justification (1 tool)

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

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_compare_models(models=["gpt-4o", "claude-3-5-sonnet", "gemini-1.5-pro"])
Model Comparison (per 1M tokens):├── gpt-4o: $2.50 in / $10.00 out├── claude-3-5-sonnet: $3.00 in / $15.00 out└── gemini-1.5-pro: $3.50 in / $10.50 out

User: Am I overpaying for my agents?→ metrx_compare_models(models=["gpt-4o", "claude-3-5-sonnet", "gemini-1.5-pro"])
Model Comparison (per 1M tokens):├── gpt-4o: $2.50 in / $10.00 out├── claude-3-5-sonnet: $3.00 in / $15.00 out└── gemini-1.5-pro: $3.50 in / $10.50 out

"Test a cheaper model"

User: Test Claude 3.5 Sonnet against my GPT-4 setup→ 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 SonnetCheck back in 14 days for statistical significance.

User: Test Claude 3.5 Sonnet against my GPT-4 setup→ 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 SonnetCheck back in 14 days for statistical significance.

Companion Tool: Cost Leak Detector

This repo also includes @metrxbot/cost-leak-detector — a free, offline CLI that scans your LLM API logs for wasted spend. No signup, no cloud, no data leaves your machine.

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.

*Not required if you've run --auth — the key is read from ~/.metrxrc automatically.

CLI Flags

Rate Limiting

60 requests per minute per tool. For higher limits, contact [email protected].

Development

bash

git clone https://github.com/metrxbots/mcp-server.gitcd mcp-servernpm installnpm run typechecknpm test

git clone https://github.com/metrxbots/mcp-server.gitcd mcp-servernpm installnpm run typechecknpm test

Contributing

See CONTRIBUTING.md for guidelines.

A Note on Naming

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 — just a GitHub namespace constraint.

License

MIT — see LICENSE.

💬 Feedback

Did Metrx work for you? We'd love to hear it — good or bad.

GitHub Discussions: Start a thread — questions, ideas, what you're building
Bug reports: Open an issue
Quick feedback: Drop a comment on our Product Hunt listing

If you installed but hit a snag, tell us what happened — we read every report.

Source: README.md at commit fcf7192

Tools

SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

v0.2.2LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
DescriptionRequired15 pts
Logo10 pts
Documentation15 pts
License10 pts

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`)

Flag	Description
`--demo`	Start with sample data — no API key or signup needed
`--auth`	Interactive login — opens browser, validates key, saves to `~/.metrxrc`
`--test`	Verify your API key and connection