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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.
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
SOC 직업 분류 기준
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/databuddy-analytics/Databuddy --skill databuddy명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SKILL.md 표시 중
Work inside the Databuddy monorepo for internal implementation, debugging, review, and refactoring. Use only for repository code changes across dashboard, api, basket, links, docs, uptime, SDK, tracker, auth, RPC, database schema, ClickHouse, or shared packages. Do not use for external SDK, API, CDN, feature flag, or LLM observability integration guidance; use databuddy instead.
Use whenever the Databuddy MCP server is available and the user wants analytics, errors, vitals, investigations, flags, links, annotations, funnels, or goals queried or changed. Covers get_data, capabilities, get_schema, the investigation lifecycle, and workspace mutations. Not for SDK integration help (use databuddy) or monorepo implementation (use databuddy-internal).
Help external users integrate Databuddy into their own apps. Use for SDK setup, React/Vue/vanilla browser tracking, Node/server event tracking, custom event planning, attribution, feature flag evaluation, experiments, Databuddy DevTools, REST analytics queries, and event ingestion. Do not use for Databuddy monorepo implementation work; use databuddy-internal.
| name | databuddy |
| description | 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. |
| metadata | {"author":"databuddy","version":"2.3"} |
Databuddy is a privacy-first analytics platform. This skill covers both the SDK (@databuddy/sdk) and the REST API.
For the most up-to-date documentation, fetch: https://databuddy.cc/llms.txt
Use this skill when:
| Import Path | Environment | Description |
|---|---|---|
@databuddy/sdk | Browser (Core) | Core tracking utilities and types |
@databuddy/sdk/react | React/Next.js | React component and hooks |
@databuddy/sdk/node | Node.js/Server | Server-side tracking with batching |
@databuddy/sdk/vue | Vue.js | Vue plugin and composables |
@databuddy/sdk/ai/vercel | AI/LLM | Vercel AI SDK middleware for LLM analytics |
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>
);
}
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();
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 />;
}
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
| Option | Type | Default | Description |
|---|---|---|---|
clientId | string | Auto-detect | Project client ID |
disabled | boolean | false | Disable all tracking |
trackWebVitals | boolean | false | Track Web Vitals metrics |
trackErrors | boolean | false | Track JavaScript errors |
trackPerformance | boolean | true | Track performance metrics |
enableBatching | boolean | true | Enable event batching |
samplingRate | number | 1.0 | Sampling rate (0.0-1.0) |
skipPatterns | string[] | — | Glob patterns to skip tracking |
<Databuddy
disabled={process.env.NODE_ENV === "development"}
clientId="..."
/>
<Databuddy
clientId="..."
skipPatterns={["/admin/**", "/internal/**"]}
maskPatterns={["/users/*", "/orders/*"]}
/>
// 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 },
});
// Browser
window.databuddy?.setGlobalProperties({
plan: "enterprise",
abVariant: "checkout-v2",
});
// Node.js
client.setGlobalProperties({
environment: "production",
version: "1.0.0",
});
| Service | URL | Purpose |
|---|---|---|
| Analytics API | https://api.databuddy.cc/v1 | Query analytics data |
| Event Tracking | https://basket.databuddy.cc | Send custom events |
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
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:
| Type | Description |
|---|---|
summary | Overall website metrics and KPIs |
pages | Page views and performance by URL |
traffic | Traffic sources and referrers |
browser_name | Browser usage breakdown |
device_types | Device category breakdown |
countries | Visitors by country |
errors | JavaScript errors |
performance | Web vitals and load times |
custom_events | Custom event data |
Date Presets: today, yesterday, last_7d, last_30d, last_90d, this_month, last_month
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 IDsget_data – Pre-built query with websiteId, type, and preset or from/toget_schema – ClickHouse schema docs (tables, columns)capabilities – Query types with descriptions, date presets, hintsDate 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.
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"
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"
For detailed documentation, see:
packages/sdk/apps/api/apps/docs/content/docs/api/