4 posts tagged with "Features"

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.

If you've ever installed an app on your computer—double-clicking a .dmg file on Mac or a .exe on Windows—you already understand .mcpb files.

Anthropic introduced the .mcpb extension (MCP Bundle) as the standard packaging format for distributing MCP servers. Think of it as the "app bundle" for AI tools: one file that contains everything needed to give your AI assistant new capabilities.

If you've used AI assistants, you've probably hit this frustration: you need to re-explain context every time you start a new conversation. That database schema you carefully described yesterday? Gone. The code snippet you asked about last week? You're pasting it in again.

MCP Resources solve this. They let you give your AI access to files and data that persist across conversations — like giving your assistant a file cabinet instead of asking them to memorize everything.