Staats vs TrackMCP: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Staats and TrackMCP — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Staats

Freemium

Agent-native, cookieless website analytics delivered through MCP, so your coding agent measures deploys and reports results in chat.

Native MCP Support: Built on the open Model Context Protocol so Claude Code, Cursor, Windsurf and Codex can query and configure analytics out of the box.
Autonomous Instrumentation: The agent adds tracking while writing features, needing only one HTML data attribute per button click and no extra JavaScript.
Ship & Measure: Every deploy is tagged automatically, then before-and-after metrics are compared so you can tell whether a change moved the needle.
Zero-Cookie Tracker: A ~1.5KB script with no cookies and no IP logging, so no cookie banner is required and tracking works the moment it is dropped in.
Drop-Off Funnels: Maps visitor journeys from landing page to checkout, pinpoints where users leak out, and suggests which step to fix next.
Anomaly Alerts: Traffic surges, viral social spikes and referrer anomalies are traced to their source and surfaced with context rather than raw numbers.
In-Chat Intelligence: Ask about visitors, top referrers and conversions inside your editor chat instead of opening a separate analytics tab.
Portfolio Overview: One account key covers every side project, letting you compare sites side by side or spin up tracking for a new app from chat.

Deploy Verification: Tag a release and have the agent compare traffic and conversion metrics before and after to confirm the change helped.
Launch Monitoring: Ask the agent how a Product Hunt or Hacker News launch is performing and get referrer-level attribution without opening a dashboard.
Funnel Debugging: Map a signup or checkout flow, find the step where visitors drop off, and get a concrete suggestion for what to fix.
Privacy-First Analytics: Replace cookie-based analytics on an EU-facing site with a cookieless tracker that avoids consent banners entirely.
Indie Portfolio Management: Track a dozen side projects under a single key and compare their traffic side by side from one chat session.
Agent-Driven Instrumentation: Let a coding agent add click tracking to new features as it writes them, so instrumentation never lags behind the code.

Freemium

Analytics for MCP servers — see which AI clients connect, which tools they call, whether the work completes and what to fix.

One-line install: Drop the @trackmcp/sdk into an existing TypeScript or Python MCP server with no manual event tagging
Client breakdown: See the share of traffic coming from Claude, Cursor, ChatGPT and custom agents
Tool analytics: Per-tool call volume, adoption, latency percentiles and health status ranked in one table
Workflow paths: Follow sessions from first request to result and see exactly where they stop
Outcome tracking: Completion rates, sessions that reached a tool and returning clients within seven days
Hidden-error detection: Flags calls that report 200 OK while returning isError, with retry counts and a suggested fix
Real-time dashboard: Events appear as they happen across production and staging environments
Alerts: Slack and webhook notifications when a tool starts failing or a workflow degrades

An MCP server author finds out which of their tools agents actually call and which have never been used
A team diagnoses why a checkout workflow stops at 38% instead of completing, by replaying the session path
A maintainer catches a tool failing 94% of calls behind a 200 OK response that logs never surfaced
A product team measures whether new clients keep coming back within seven days of first connecting
An engineer compares latency and error rates across production and staging before shipping a schema change
A company decides which MCP tools to invest in by ranking them on adoption rather than guesswork