AI agent skills for marketing analytics, attribution, campaign reporting, web analytics, and growth dashboards.
Marketing Analytics & Reporting tools are AI-powered software designed to help developers and teams tackle marketing analytics & reporting-related tasks more efficiently. These tools are typically published as open-source projects on GitHub and can be integrated into existing workflows via MCP (Model Context Protocol), Claude Skills, or standalone agent frameworks. On Agent Skills Hub, we index 25 quality-scored marketing analytics & reporting tools across languages including Python, Kotlin, TypeScript.
In 2026, the AI agent ecosystem is maturing rapidly. Marketing Analytics & Reporting tools can significantly boost development efficiency by automating repetitive tasks, reducing human error, and providing intelligent suggestions. The top 3 tools — google-analytics-mcp, facebook-ads-library-mcp, facebook-ads-library-mcp — have earned an average of 8,091 GitHub stars, reflecting strong community validation. 18 of the listed tools come with clear open-source licenses, ensuring freedom to use and modify.
When choosing a marketing analytics & reporting tool, consider these factors: 1) Community activity — GitHub stars and recent commit frequency indicate reliability; 2) Integration method — check if it supports MCP, Claude, or your preferred agent framework; 3) Language compatibility — the most common language in this list is Python; 4) Quality score — Agent Skills Hub's composite score evaluates code quality, documentation completeness, and maintenance activity. Our recommendation: start with google-analytics-mcp — it ranks highest in both star count and quality score.
Google Analytics 4 data to AI agents, agentic workflows, and MCP clients. Give agents analysis-ready access to website traffic, user behavior, and performance data with schema discovery, server-side aggregation, and safe defaults that reduce data wrangling.
MCP Server for Facebook ADs Library - Get instant answers from FB's ad library
MCP Server for Facebook ADs Library - Get instant answers from FB's ad library
Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce — the server blocks the call if they don't. Works with any MCP-compatible client.
The AI command center for Google Ads, Analytics and Search Console.
Build LLM agents that explain why, not just what. Attribution-driven agent requirements engineering framework. Based on the 4D-ARE Paper - https://arxiv.org/abs/2601.04556
AI-powered GA4 + GTM event tracking — automates site analysis, event schema, GTM sync, preview verification, and publishing. Works with Cursor, Codex, and any AI agent.
AI-powered GA4 + GTM event tracking — automates site analysis, event schema, GTM sync, preview verification, and publishing. Works with Cursor, Codex, and any AI agent.
An opinionated Claude Code Plugin Pack. Skills, Agents, Hooks, MCPs. Examples: Email draft preview assistance & humanisation. Agents for Codex and Gemini "outsourcing". Skills for Google Analytics & Google Tag Manager, Shopify and much more
Marketing skills for Claude Code and AI agents. CRO, copywriting, SEO, analytics, and growth engineering.
:hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP.
AI Data Vault - A query engine for AI Agents to securely query data from any datasource
Platform dedicated to building an open foundation for applied Artificial Intelligence, designed for people seeking production-ready AI systems they can truly control, extend and deploy anywhere.
Real-time Claude Code usage monitor with predictions and warnings
UAParser.js - The Essential Web Development Tool for User-Agent Detection. Detect Browsers, OS, Devices, Bots, Apps, AI Crawlers, and more. Run in Browser (client-side) or Node.js (server-side).
end to end app store screenshot creation using AI
Laminar - open-source observability platform purpose-built for AI agents. YC S24.
120 marketing skills + 8 commands for Claude Code & AI agents across 7 disciplines — SEO/GEO, influencer, paid ads, email, product launch, organic social & brand narrative — on one shared contract, with 8 auditor gates: CORE-EEAT · CITE · STAR · ROAS · SEND · RAMP · ECHO · TALE.
Agentic Email Automation Tool: Describe your product. Define your target market. The AI finds the leads for you.
Observal is a local registry and analytics platform for your AI components. Setup Observal, define the scope and share your Skills, MCPs and Agents.
Observal is a local registry and analytics platform for your AI components. Setup Observal, define the scope and share your Skills, MCPs and Agents.
AI agent skills for App Store Optimization (ASO) and app marketing. Built for indie developers, app marketers, and growth teams who want Cursor, Claude Code, or any Agent Skills-compatible AI assistant to help with keyword research, metadata optimization, competitor analysis, and app growth.
One SQL interface for 60+ tools (e.g., GitHub, Notion, Airtable). Plug into any LLM through MCP.
Wondel.ai Agent Skills — Business, Marketing, UX & Coding Frameworks from Bestselling Books. 50 skills + 12 guided journeys for Claude Code, Codex, Cursor & other agentskills.io agents.
Route, manage, and analyze your LLM requests across multiple providers with a unified API interface.
| Tool | Stars | Language | License | Score |
|---|---|---|---|---|
| google-analytics-mcp | ★ 229 | Python | Apache-2.0 | 68 |
| facebook-ads-library-mcp | ★ 257 | Python | MIT | 71 |
| facebook-ads-library-mcp | ★ 189 | Python | MIT | 51 |
| task-orchestrator | ★ 197 | Kotlin | MIT | 71 |
| adloop | ★ 222 | Python | MIT | 65 |
| 4D-ARE | ★ 181 | Python | MIT | 57 |
| analytics-tracking-automation | ★ 120 | TypeScript | Apache-2.0 | 62 |
| event-tracking-skill | ★ 118 | TypeScript | Apache-2.0 | 56 |
| wookstar-claude-plugins | ★ 73 | Python | — | 73 |
| marketingskills | ★ 41.4k | JavaScript | MIT | 87 |
| posthog | ★ 37.3k | Python | — | 73 |
| mindsdb | ★ 39.1k | Python | — | 70 |
| minds-platform | ★ 39.2k | Python | — | 66 |
| Claude-Code-Usage-Monitor | ★ 8.4k | Python | MIT | 79 |
| ua-parser-js | ★ 10.2k | JavaScript | AGPL-3.0 | 70 |
| app-store-screenshots | ★ 6.2k | TypeScript | MIT | 71 |
| lmnr | ★ 3.1k | TypeScript | Apache-2.0 | 70 |
| aaron-marketing-skills | ★ 2.5k | Python | Apache-2.0 | 72 |
| OpenOutreach | ★ 2.5k | Python | — | 69 |
| Observal | ★ 2.2k | Python | Apache-2.0 | 72 |
| Observal | ★ 2.1k | Python | AGPL-3.0 | 69 |
| aso-skills | ★ 1.5k | Shell | MIT | 78 |
| anyquery | ★ 1.7k | Go | — | 71 |
| skills | ★ 1.7k | Shell | MIT | 71 |
| llmgateway | ★ 1.5k | TypeScript | — | 68 |
The top marketing analytics & reporting tools in 2026 are google-analytics-mcp, facebook-ads-library-mcp, facebook-ads-library-mcp. Agent Skills Hub ranks 25 options by GitHub stars, quality score (6 dimensions including completeness, examples, and agent readiness), and recent activity. The list is rebuilt every 8 hours from live GitHub data.
google-analytics-mcp (229 stars) is the most adopted choice for general marketing analytics & reporting workflows, written in Python. facebook-ads-library-mcp (257 stars) is a strong alternative. Pick by your existing stack: match the language and runtime your team already uses to minimize integration cost. If unsure, start with google-analytics-mcp — it has the deepest community and the most examples online.
Avoid pre-built marketing analytics & reporting tools when (1) your use case requires deep customization that the tool's plugin system doesn't support, (2) you have strict compliance requirements that ban third-party dependencies, (3) the tool's maintenance is inactive (last commit >6 months ago), or (4) your data volume is small enough that a 50-line custom script is cheaper than learning the tool. For most production workflows above 100 requests/day, the time savings from a maintained tool outweigh the customization loss.
Marketing Analytics & Reporting focuses specifically on ai agent skills for marketing analytics, attribution, campaign reporting, web analytics, and growth dashboards. Data Visualization is a related but distinct category — see https://agentskillshub.top/best/data-visualization/ for those tools. The two often appear in the same agent pipeline but solve different problems: choose marketing analytics & reporting when your primary goal is the specific task, and data visualization when the workflow is broader.
For most teams, yes. google-analytics-mcp has 229 stars worth of community testing, handles edge cases you haven't thought of, and ships with documentation. Build your own only when (1) your requirements are deeply non-standard, (2) you have a security/compliance reason to avoid OSS dependencies, or (3) the maintenance burden is small enough (<200 lines of code) that you'll save time long-term. The break-even point is usually around 2-3 weeks of dev time saved.
Most marketing analytics & reporting tools listed are open source under permissive licenses (MIT, Apache 2.0). A handful offer paid managed/cloud versions on top of free self-hosted core. Always check the LICENSE file on each tool's GitHub repository before commercial use — some use AGPL or non-commercial restrictions that may not fit your deployment model.
