SEO became a standardized industry discipline pretty much after Google dominated the market and stabilized the rules of engagement. The search engine giants evole their ranking algorithms mostly to fight exploiting of their mechanims, the core principles of SEO don't change much.
In contrast, LLMs are still constantly evolving. Not only the models, the way of agents doing things, the tools/skills agent shall use, the whole system may be completely different next month. GEO is merely an attempt to ride the LLM hype，clumsily stitching together unrelated concepts.
The ruling is not that Google can never have exclusive contracts for anything. If they rent Moscone Center for an event, there's no requirement that others be allowed to use the same space at the same time.
And there is no exclusive contract between Google and users with regards to sources of apps. It's a change in technical requirements for the platform.
In law, the actual thing matters; just being able to draw vague parallels doesn't mean anything.
This article will show you how to call a MCP server in the shell, without mcp dev or any third party tools, only with echo > or copying/pasting JSONRPC message directly.
For the OAuth part, the access_token is all an MCP server needs. So users could do an OAuth Authorization like in the settings or by the chatbot, and let MCP servers handle the storage of the access_token.
For remote MCP servers, storing access_token is a very common practice. For MCP servers hosted locally, how to deal with a bunch of secret keys is a problem.
> In the late 20th century, democracies usually outperformed dictatorships, because they were far better at processing information. We tend to think about the conflict between democracy and dictatorship as a conflict between two different ethical systems, but it is actually a conflict between two different data-processing systems. Democracy distributes the power to process information and make decisions among many people and institutions, whereas dictatorship concentrates information and power in one place. Given 20th-century technology, it was inefficient to concentrate too much information and power in one place.
> However, artificial intelligence may soon swing the pendulum in the opposite direction. AI makes it possible to process enormous amounts of information centrally. In fact, it might make centralized systems far more efficient than diffuse systems, because machine learning works better when the machine has more information to analyze. If you disregard all privacy concerns and concentrate all the information relating to a billion people in one database, you’ll wind up with much better algorithms than if you respect individual privacy and have in your database only partial information on a million people.
May be the case is that filtering user by browser UA is no longer a feasible solution(new browsers and alike are growing), and neither running javascript(headless chrome everywhere).
For local physical store, geo-location is a naturally filter for customers as long as beaming a person from a spaceship to earth is not invented. For web, a equally effective solution is very hard to find.
In contrast, LLMs are still constantly evolving. Not only the models, the way of agents doing things, the tools/skills agent shall use, the whole system may be completely different next month. GEO is merely an attempt to ride the LLM hype，clumsily stitching together unrelated concepts.