Harvest has been the go-to time tracking tool for freelancers, agencies, and development teams for years. Whether you're billing clients hourly, managing project budgets, or just trying to understand where your time actually goes, Harvest makes it all work.

But here's the problem: your AI assistants have been locked out of this valuable data. Sure, you could export reports and paste them into ChatGPT, but that's not real integration. That's not having your AI actually understand and work with your time data.

That's why we built the Harvest MCP bundle.

Most teams now have an AI that can call tools, but someone has to keep those tools healthy. That someone is the MCP Engineer. They own how your assistants connect, which credentials stay active, and which bundles are safe to run on any given day.

Here's the exact playbook for using our Reddit bundle to find winning ad teardowns, copy their structure, and write your own "here’s what actually worked" breakdowns.

Most people stare at a blank page wondering what to write. We're going to skip that part entirely. Instead, we'll use the Reddit bundle to find what's already working, understand why it works, and then just plug in our own data.

You can run all of this right now in Bundle Studio.

If you're using Cursor (and honestly, why wouldn't you be), you've probably heard about MCP. It's how you give Claude access to your databases, APIs, and tools right inside the editor.

Here's how to actually set it up.

Tool overload is real. Give AI 50 tools and it gets confused—slow, wrong tool selections, data dumps instead of answers. We've always solved this with focused bundles: give AI 5-15 tools for a specific workflow, and it works great.

But what about when you need data from multiple services at once?

That's why we built the Hub. It uses programmatic tool calling—AI discovers tools on-demand and writes code to orchestrate them—so you can work across all your connected services without the overload problem.

This builds on recent research from Anthropic—their work on advanced tool use and code execution with MCP. We took these patterns and made them accessible to anyone with an MCPBundles account.

Ask your AI about pipeline data and get a real dashboard. Not text. Not a description. An actual interactive visualization you can click, filter, and explore.

The Model Context Protocol just got a major upgrade. MCP Apps (SEP-1865) is a new extension that lets MCP servers deliver interactive user interfaces directly to AI applications like Claude, ChatGPT, or Cursor.

This isn't just about pretty visuals. It's about giving your AI tools the ability to show data in ways that actually make sense—charts, tables, dashboards, forms—while maintaining the security and auditability that MCP was built on.

Deal flow management is messy. You're tracking companies, founders, opportunities, lists, notes, emails, meetings, calls. Jumping between screens trying to find who you talked to last week, what stage that deal is in, which companies need follow-up.

We built 35+ MCP tools for Affinity. Now you can manage your entire relationship intelligence workflow through conversation with Claude. Track companies, find people, manage opportunities, organize lists, review interactions. Just ask.

So we built an integration for Cursor's Cloud Agents API. Not because it was on some roadmap or anything. We did it because Cursor's literally our favorite coding tool and we use it every single day.

Google Analytics is overkill for most sites. You just want to know how many people visited, where they came from, and which pages they read. Instead you get 50 different reports, cookie consent banners everywhere, and a dashboard that takes five minutes to load.

So we built 17 MCP tools for Plausible Analytics. Now you can check your site stats through conversation with Claude. Simple, privacy-focused analytics without the complexity. No cookies, no invasive tracking, no endless dashboards.