5 posts tagged with "Releases"

TL;DR​

• MCPBundles Desktop is a menu-bar app that replaces the old pip install + terminal proxy setup from our March Obsidian guide.
• Install it, pair your workspace once, and AI in Studio, ChatGPT, or Cursor can read and write your vault while Obsidian stays on your machine — nothing copied to our servers.

Picture Friday evening. Obsidian is open on your Mac. You're in MCPBundles Studio asking for open tasks tagged #work. That only works if something on your computer is connected and listening. That's what Desktop does — it sits in the menu bar and keeps the link alive so you don't have to think about it.

TL;DR​

~22s → ~0.4s per production call on the MCPBundles CLI (May 2026, my Mac). Five calls back-to-back: ~110s → ~2.2s. The MCP slice of make growth-refresh-report: 15+ min → ~53s.

I run MCPBundles. I'm biased. I'm also the person who kept running a fifteen-minute Makefile every morning and telling myself that was fine because "most of it is Playwright anyway" — which was sometimes true and often a cope.

The breaking point wasn't a benchmark chart. It was last Tuesday. I ran time mcpbundles call … on a Postgres pull we'd used in growth scripts for months because I didn't believe the numbers our benchmark script printed. 0.38s wall clock. I re-ran it thinking I'd mistyped --as. Same answer. I'd been eating ~22s of local CLI overhead on every call. Not Gmail. Not the Hub. The sidecar boot path. I'd normalized it because the alternative was rewriting a Makefile I'd already rewritten twice.

Every AI platform supports MCP tools. But what happens when the tool you need doesn't exist yet? Maybe you're working with an internal API, a niche SaaS, or a service that nobody has wrapped in MCP. Until now, you'd write a custom server.

Now your AI can do it itself.

MCPBundles has always worked as an MCP server. You add it to Claude Desktop, Cursor, ChatGPT, or any MCP-compatible client, and your AI gets access to Stripe, HubSpot, Postgres, PostHog, Gmail, and every other service you've connected — with real credentials, real permissions, and real data.

The MCPBundles CLI is an alternative way to access those same tools. Instead of configuring MCPBundles as a remote MCP server in your client, you install a command-line tool and authenticate with an API key. The AI agent discovers and calls your tools through shell commands — the same 10,000+ tools, the same credentials, the same workspace permissions.

pip install mcpbundles

Today, MCP Apps are live as the first official MCP extension. Tools can now return interactive UI components that render directly in the conversation: dashboards, forms, visualizations, multi-step workflows, and more. It is ready for production.