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The FloConnector blog

Notes from the wire

Field notes on connecting AI to the software businesses run on: MCP, deferred tools, connectors, and the architecture behind FloConnector.

Featured
Engineering 9 min read

How FloConnector keeps 50+ connectors out of your context window

Loading every tool a business might need costs ~72K tokens before the model reads a word. Deferred tools flip that: the model pays only for what it reaches for. How it works, why it isn't part of MCP, and what a server can actually do about its own context cost.

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Engineering 18 min read

Code mode needs a sandbox. Query mode doesn't.

Context engineering for MCP has two named answers: deferred loading for too many tools, code execution for too much data. Code execution buys its savings with an agent sandbox. Here's the third answer I built FloConnector on instead, why I think it's the right default, and where it loses.

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Explainer 5 min read

What is an MCP server? A plain-English guide

An MCP server is the piece that lets an AI like Claude actually do things in your other software: read a spreadsheet, send an email, raise an invoice. Here's what that means, how it works, and why you probably shouldn't build one yourself.

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Security 4 min read

Your AI never sees your passwords (and it never should)

Connecting an AI to the software your business runs on means handing over the keys to your inbox, your CRM, your calendar. The one thing that should never happen is the AI ever holding those keys. Here's the credential architecture that keeps them out of the model's reach.

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Perspective 5 min read

Skills or MCP? You're asking the wrong question

The 2026 debate frames Agent Skills and MCP servers as rivals: pick one. They're not rivals. MCPs are verbs; Skills are playbooks. The interesting systems use both, and understanding why tells you a lot about where a hosted connector layer fits.

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Engineering 5 min read

More connectors, worse agent: the tool-overload trap and how to escape it

There's a counter-intuitive failure mode in agent design: adding tools past a point makes the model less reliable, not more. Here's why it happens, the numbers behind it, and the progressive-disclosure pattern that lets a workspace run dozens of connectors without paying for it.

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