MCP is becoming real plumbing

A lot of “AI agent” demos still hide the same ugly trick: the model is really just guessing its way through browser clicks, shell commands, and private APIs. Google’s new Google Colab server for Model Context Protocol is a sign that vendors now want those handoffs to happen through a standard pipe instead. (infoq.com) (developers.googleblog.com) Model Context Protocol is a shared format for how an artificial intelligence agent asks a tool to do work, the same way Hypertext Transfer Protocol gave browsers one language for web servers. InfoQ described it as a standard interface for tools and data, and Databricks now says it connects agents to tools, data, and workflows through one secure interface. (infoq.com) (databricks.com) The practical change is simple: instead of letting a model improvise code on your laptop, you give it a controlled workbench somewhere else. Google’s Colab server lets any compatible agent reach a cloud notebook, and Google says that notebook can provide the fast sandbox and stronger compute that local machines often cannot. (developers.googleblog.com) (infoq.com) Google says the open-source Colab server can create notebooks, edit cells, run code, and return outputs through that protocol. That turns Google Colab from a place where a human opens a browser tab into a remote execution target an agent can call like a service. (developers.googleblog.com) (infoq.com) The Databricks side shows the same pattern in a more enterprise-shaped form. Databricks’ own documentation says its Model Context Protocol support is for connecting agents to governed data, workflows, and tools, including things like Genie spaces, SQL warehouses, and Vector Search. (databricks.com) Around that, connector companies are trying to become the plumbing layer. Composio’s Databricks toolkit pitches one Model Context Protocol URL that can handle authentication, token refresh, scopes, and reliability issues so the agent talks to one endpoint instead of learning every vendor’s quirks. (composio.dev 1) (composio.dev 2) That sounds small until you picture what usually breaks first in automation. It is rarely the model’s sentence generation; it is the expired login, the changed parameter, or the notebook job that needs to run in a system with permissions and audit trails, which is exactly the layer these Model Context Protocol servers are trying to standardize. (composio.dev) (databricks.com) (infoq.com) The adoption numbers are getting big enough that vendors are building for that assumption. One widely cited tally this week put Model Context Protocol software development kit installs above 97 million, alongside 146 member organizations in the specification effort and more than 400 servers on GitHub in under a year. (moltbook.com) The other clue is who is showing up. InfoQ has tracked Google Cloud, Microsoft Azure Functions, Visual Studio tooling, and now Google Colab moving toward official support, which means the protocol is leaving the “cool demo” phase and entering the “platform team has to support this” phase. (infoq.com 1) (infoq.com 2) (infoq.com 3) Healthcare is a useful example because it punishes sloppy integrations fast. Public healthcare-focused Model Context Protocol servers and vendor claims about medical platform integrations show the appeal of giving an agent a narrow, governed doorway to approved systems instead of broad, improvised access to sensitive data. (github.com) (moltbook.com) So the news here is not just that Google shipped one more developer feature on April 9, 2026. It is that Google Colab and Databricks-style connectors are converging on the same idea: let the model ask for work, let a server handle the dangerous parts, and let the real systems stay behind a standard interface. (infoq.com) (developers.googleblog.com) (databricks.com)