agentskills.codes
DA

databuddy

by databuddy-analyticsData & AnalyticsSource

Provides SDKs and APIs to integrate Databuddy analytics and observability into applications.

MonitoringData AnalysisReactNext.jsNode.js

Install

mkdir -p .claude/skills/databuddy && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4882" && unzip -o skill.zip -d .claude/skills/databuddy && rm skill.zip

Installs to .claude/skills/databuddy

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Integrate Databuddy analytics using the SDK, REST API, or MCP. Use when implementing analytics tracking, feature flags, custom events, Web Vitals, error tracking, LLM observability, MCP agents, or querying analytics data programmatically.
238 chars✓ has a “when” trigger
Intermediate

Key capabilities

  • →Implement event tracking and Web Vitals
  • →Add feature flags to applications
  • →Integrate LLM observability
  • →Query analytics data via REST API
  • →Build MCP agents for analytics

How it works

The skill provides SDKs for frontend and backend tracking, and a REST API for querying aggregated analytics data.

Inputs & outputs

You give it
Tracking events or query parameters
You get back
Analytics data or tracking confirmation

When to use databuddy

  • →Implement analytics tracking
  • →Add feature flags
  • →Monitor LLM observability

About this skill

Databuddy

Databuddy is a privacy-first analytics platform. This skill covers both the SDK (@databuddy/sdk) and the REST API.

External Documentation

For the most up-to-date documentation, fetch: https://databuddy.cc/llms.txt

When to Use This Skill

Use this skill when:

  • Setting up analytics in React/Next.js/Vue applications
  • Implementing server-side tracking in Node.js
  • Adding feature flags to an application
  • Tracking custom events, errors, or Web Vitals
  • Integrating LLM observability with Vercel AI SDK
  • Querying analytics data via the REST API or MCP
  • Building MCP agents or AI-powered analytics workflows
  • Building custom dashboards or reports

SDK Entry Points

Import PathEnvironmentDescription
@databuddy/sdkBrowser (Core)Core tracking utilities and types
@databuddy/sdk/reactReact/Next.jsReact component and hooks
@databuddy/sdk/nodeNode.js/ServerServer-side tracking with batching
@databuddy/sdk/vueVue.jsVue plugin and composables
@databuddy/sdk/ai/vercelAI/LLMVercel AI SDK middleware for LLM analytics

Quick Start

React/Next.js

import { Databuddy } from "@databuddy/sdk/react";

export default function RootLayout({ children }) {
  return (
    <html>
      <body>
        {children}
        <Databuddy
          clientId={process.env.NEXT_PUBLIC_DATABUDDY_CLIENT_ID}
          trackWebVitals
          trackErrors
          trackPerformance
        />
      </body>
    </html>
  );
}

Node.js Server-Side

import { Databuddy } from "@databuddy/sdk/node";

const client = new Databuddy({
  clientId: process.env.DATABUDDY_CLIENT_ID,
  enableBatching: true,
});

await client.track({
  name: "api_call",
  properties: { endpoint: "/users", method: "GET" },
});

// Important: flush before process exit in serverless
await client.flush();

Feature Flags

import { FlagsProvider, useFlag, useFeature } from "@databuddy/sdk/react";

// Wrap your app
<FlagsProvider clientId="..." user={{ userId: "123" }}>
  <App />
</FlagsProvider>

// In components
function MyComponent() {
  const { on, loading } = useFeature("dark-mode");
  if (loading) return <Skeleton />;
  return on ? <DarkTheme /> : <LightTheme />;
}

LLM Analytics

import { databuddyLLM } from "@databuddy/sdk/ai/vercel";
import { openai } from "@ai-sdk/openai";

const { track } = databuddyLLM({
  apiKey: process.env.DATABUDDY_API_KEY,
});

const model = track(openai("gpt-4o"));
// All LLM calls are now automatically tracked

Key Configuration Options

OptionTypeDefaultDescription
clientIdstringAuto-detectProject client ID
disabledbooleanfalseDisable all tracking
trackWebVitalsbooleanfalseTrack Web Vitals metrics
trackErrorsbooleanfalseTrack JavaScript errors
trackPerformancebooleantrueTrack performance metrics
enableBatchingbooleantrueEnable event batching
samplingRatenumber1.0Sampling rate (0.0-1.0)
skipPatternsstring[]—Glob patterns to skip tracking

Common Patterns

Disable in Development

<Databuddy
  disabled={process.env.NODE_ENV === "development"}
  clientId="..."
/>

Skip Sensitive Paths

<Databuddy
  clientId="..."
  skipPatterns={["/admin/**", "/internal/**"]}
  maskPatterns={["/users/*", "/orders/*"]}
/>

Custom Event Tracking

// Browser
import { track } from "@databuddy/sdk/react";

track("purchase", {
  product_id: "sku-123",
  amount: 99.99,
  currency: "USD",
});

// Node.js
await client.track({
  name: "subscription_renewed",
  properties: { plan: "pro", amount: 29.99 },
});

Global Properties

// Browser
window.databuddy?.setGlobalProperties({
  plan: "enterprise",
  abVariant: "checkout-v2",
});

// Node.js
client.setGlobalProperties({
  environment: "production",
  version: "1.0.0",
});

REST API

Base URLs

ServiceURLPurpose
Analytics APIhttps://api.databuddy.cc/v1Query analytics data
Event Trackinghttps://basket.databuddy.ccSend custom events

Authentication

Use API key in the x-api-key header:

curl -H "x-api-key: dbdy_your_api_key" \
  https://api.databuddy.cc/v1/query/websites

Get API keys from: Dashboard → Organization Settings → API Keys

Query Analytics Data

curl -X POST -H "x-api-key: dbdy_your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "parameters": ["summary", "pages"],
    "preset": "last_30d"
  }' \
  "https://api.databuddy.cc/v1/query?website_id=web_123"

Available Query Types:

TypeDescription
summaryOverall website metrics and KPIs
pagesPage views and performance by URL
trafficTraffic sources and referrers
browser_nameBrowser usage breakdown
device_typesDevice category breakdown
countriesVisitors by country
errorsJavaScript errors
performanceWeb vitals and load times
custom_eventsCustom event data

Date Presets: today, yesterday, last_7d, last_30d, last_90d, this_month, last_month

MCP (Model Context Protocol)

Databuddy exposes an MCP server for AI agents (Cursor, Claude Desktop, etc.) to query analytics. Use for natural-language questions, automated reports, or structured data extraction.

Endpoint: POST https://api.databuddy.cc/v1/mcp (local: http://localhost:3001/v1/mcp)

Auth: API key with read:data scope via x-api-key or Authorization: Bearer <key>

Tools:

  • ask – Natural-language analytics questions (e.g. "top 5 pages last week")
  • list_websites – List accessible website IDs
  • get_data – Pre-built query with websiteId, type, and preset or from/to
  • get_schema – ClickHouse schema docs (tables, columns)
  • capabilities – Query types with descriptions, date presets, hints

Date presets for get_data: last_7d, last_30d, last_90d, today, yesterday, this_week, this_month, etc.

Cursor setup (mcp.json): Add a Databuddy MCP entry with the API URL and your API key.

Send Events via API

curl -X POST \
  -H "Content-Type: application/json" \
  -d '{
    "type": "custom",
    "name": "purchase",
    "properties": {
      "value": 99.99,
      "currency": "USD"
    }
  }' \
  "https://basket.databuddy.cc/?client_id=web_123"

Batch Events

curl -X POST \
  -H "Content-Type: application/json" \
  -d '[
    {"type": "custom", "name": "event1", "properties": {...}},
    {"type": "custom", "name": "event2", "properties": {...}}
  ]' \
  "https://basket.databuddy.cc/batch?client_id=web_123"

Reference Documentation

For detailed documentation, see:

Source Code

  • SDK: packages/sdk/
  • API: apps/api/
  • API Docs: apps/docs/content/docs/api/

When not to use it

  • →Tracking non-web applications
  • →Storing sensitive PII without masking

Prerequisites

Databuddy client IDAPI key for REST access

Limitations

  • →Requires SDK integration in source code
  • →API access requires valid API keys

How it compares

This platform integrates tracking, feature flags, and LLM observability into a single privacy-first analytics solution.

Compared to similar skills

databuddy side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
databuddy (this skill)13moCautionIntermediate
skills06moNo flagsIntermediate
senior-fullstack357moReviewIntermediate
posthog-analytics34moReviewIntermediate

Try saying

Example prompts that trigger this skill in your AI assistant.

You might also like

skills

xDaijobu

How to work with TLS Watch - a TLS certificate monitoring application

00

senior-fullstack

davila7

Comprehensive fullstack development skill for building complete web applications with React, Next.js, Node.js, GraphQL, and PostgreSQL. Includes project scaffolding, code quality analysis, architecture patterns, and complete tech stack guidance. Use when building new projects, analyzing code quality, implementing design patterns, or setting up development workflows.

35110

posthog-analytics

alinaqi

PostHog analytics, event tracking, feature flags, dashboards

39

ai-sdk-documentation

malob

This skill should be used when working with Vercel AI SDK, AI Gateway, streamText, generateText, generateObject, streamObject, tool calling, or AI SDK providers. Also relevant for "ai-sdk", "@ai-sdk/*" packages, or questions about AI SDK patterns, configuration, and best practices.

13

clerk-install-auth

jeremylongshore

Install and configure Clerk SDK/CLI authentication. Use when setting up a new Clerk integration, configuring API keys, or initializing Clerk in your project. Trigger with phrases like "install clerk", "setup clerk", "clerk auth", "configure clerk API key", "add clerk to project".

12

senior-qa

diegosouzapw

Comprehensive QA and testing skill for quality assurance, test automation, and testing strategies for ReactJS, NextJS, NodeJS applications. Includes test suite generation, coverage analysis, E2E testing setup, and quality metrics. Use when designing test strategies, writing test cases, implementing

00

Search skills

Search the agent skills registry