I think MCP is the right place to declare the context management API; the C in MCP is Context. As far as building goes, you could build a (universal) context store. I guess the value would be to bring the context closer to the model?
The value is building the context itself.
Using MCP, this could be a method that would get the context to take decisions.
For example, here's an example of how I use it currently:
```
const context = await getContext();
const response = await generateText({ system: `Here's the user context: ${context}`, messages: [...] });
console.log(context);
// "First-time visitor using Google Chrome on a MacBook, browsing from San Francisco.
// Landed on the pricing page from a Google ad, clicked to compare plans,
// then visited the enterprise section before initiating a support chat."
```
It's like a session recorder for LLMs that captures rich user behavior and traits (like device, browser, location, and journey) and turns them into LLM context. Your agent or app instantly becomes more helpful, relevant, and aware without wiring up your own tracking and enrichment pipeline.
A context inference service sounds valuable but I wonder what your moat would be.