Here's an uncomfortable question: Where does API integration actually start?
If you answered "from the developer portal," you're answering yesterday's question. Your beautifully designed portal lives in a browser tab that developers visit once, maybe twice. But the actual integration starts in their IDE, surrounded by their codebase, their problems, and now their AI coding assistant doing its job.
The gap between where you deliver API context and where developers actually need it has never been wider.
The API developer experience industry has come far. From PDF documentation to interactive portals like Stripe and Twilio, then chatbots for quick answers, and most recently, the LLMs.txt standard to make documentation AI-friendly. Each innovation solved a real problem, but they all made the same assumption: developers would come to the portal, consume information, and return to their IDE to implement it.
That assumption is breaking down. In the age of AI assistants, the constant back and forth between the portal and the IDE has become a friction point nobody has addressed.
Cursor, GitHub Copilot, and AI coding assistants moved from experiment to daily workflow in just two years. These tools can spin up entire applications and write complex algorithms in seconds. Yet they fail spectacularly at API integrations.
Why? LLMs are trained on historical data. They don't know about your API's latest version or its SDKs. They can't see the idiomatic patterns your SDKs generate. They lack the rules governing the correct API consumption.
The result? A developer asks their AI assistant to "integrate the payment API," and it confidently generates code based on outdated documentation or generic patterns that don't match your SDK conventions. The code compiles. It might even work. But it introduces security vulnerabilities or inefficient patterns that create problems months later.
The frustration is real: "Why can my AI assistant write a binary search tree in seconds but can't figure out how to call your API correctly?"
The problem isn't that developer portals are bad. They're just in the wrong place.
Developers are in their IDEs, writing code, asking their AI assistant for help. They need context right there, in that moment. Switching to a browser, reading documentation, and then translating it back into code creates friction that compounds with every API call.
Even LLMs.txt on your developer portals doesn't solve this. It provides static documentation in a machine-readable format, but not what developers actually need: SDK-aware, idiomatic code patterns that match their language and framework, with rules for correct implementation.
APIMatic saw this gap. Instead of just making documentation more accessible, what if we brought the actual SDK-generated patterns directly into the IDE where developers are already working?
It's a one-click MCP Server install that changes how API context reaches developers in their AI-assisted IDEs.
Here's the flow: APIMatic takes your API specification and generates SDKs and documentation like always. Then it does something different. It converts that documentation and SDK package details into a structured MCP (Model Context Protocol) server that delivers SDK-native context directly into Cursor.
This isn't just documentation about how the API works. The MCP server provides context derived from actual SDK code. The idiomatic patterns. The proper error handling. The authenticated request structure. All packaged specifically for AI assistants to understand and apply correctly.
See it in action: Watch how a developer goes from documentation to working integration in under 2 minutes.
Internal testing shows what happens when developers have SDK-aware context directly in their IDE:
Token efficiency jumps 37%. AI assistants accomplish the same task with significantly fewer tokens—faster responses, lower costs, and more efficient development cycles.
Scalable Integration success hits 83%. Complex APIs perform even better because complexity is where the gap between generic patterns and idiomatic SDK usage matters most.
Code quality improves measurably—about 70% fewer security issues per thousand lines of code. Composite code quality scores run 30% higher on average. The code doesn't just work; it's structured the way it should be.
The harder-to-measure impact? Developers stop fighting with API integration and start focusing on business logic. No context switching between the IDE and the portal. No debugging why AI-generated code doesn't match SDK patterns. Just building features.
The architecture becomes more uniform and modular—faster maintenance, easier scaling. The productivity gain compounds over time.
Here's the question your developer experience strategy needs to answer: Where does your API's developer experience actually live?
If the answer is "on our portal," you're solving 2015's problem. The new battleground is inside Cursor, VS Code, and whatever IDE your developers open every morning. That's where they spend eight hours a day. That's where they ask AI assistants for help. That's where your API context needs to be.
This isn't about abandoning developer portals. They still matter for onboarding, reference material, and community building. But they can't be the only place your API context lives when the actual integration work happens somewhere else entirely.
APIMatic Context Plugins are now available for Cursor, with VS Code and v0 integrations coming next. It works with your existing API specifications and SDK generation workflow. One-click MCP Server install bridges the gap between where your API context lives and where developers actually need it.
Request a Demo to see how SDK-generated context changes the integration experience.