Most API companies eventually face the same question: should we build an SDK, and if so, how? The answer isn't obvious because SDKs represent a significant engineering investment that can either accelerate developer adoption or become a maintenance nightmare.
This guide walks through the practical decisions API companies need to make when implementing SDKs. You'll learn why SDKs matter beyond simple API wrappers, how to choose between building from scratch versus generation, which languages to prioritize, and how to maintain SDKs without drowning your team in busywork.
Why your API needs an SDK
An SDK, or Software Development Kit, is a set of tools and libraries that allows developers to use your API in their native programming language. For API companies, providing an SDK is no longer a nice-to-have; it is a critical part of the developer experience that directly impacts how quickly users can integrate and how much trust they place in your platform. The largest API-first companies like Stripe, Twilio, and OpenAI all invest heavily in first-class, official SDKs because they understand that your API isn’t finished until the SDK ships.
A great SDK lets users focus on discovering and using your API, cutting the time they spend on irrelevant implementation details. When a developer can make their first successful API call in minutes, they are far more likely to convert into a paying customer and build on top of your platform. Omitting an SDK forces every developer to reinvent the wheel, increasing their integration time and your support load.
How SDKs amplify your API investment
An SDK is much more than a simple wrapper around your REST or GraphQL endpoints. It transforms raw HTTP requests into a language-native interface that feels intuitive to developers. This unlocks a higher level of productivity and reliability.
A well-built SDK handles tedious boilerplate like authenticating requests, retrying failed calls, and paginating through large result sets automatically. It provides rich type-safety, which means developers get features like IDE autocomplete and can catch errors at compile time instead of runtime.
SDKs also provide a standardized way to collect high-fidelity analytics. By including a consistent set of headers on every request, you can understand which languages, runtimes, and SDK versions your customers are using. This data is invaluable for diagnosing issues and making informed decisions about your product roadmap.
Three paths to SDK implementation
When deciding to build an SDK, you have three main paths. Each comes with different trade-offs in cost, control, speed, and ongoing maintenance.
Implementation Path | Cost | Control | Speed | Maintenance |
|---|---|---|---|---|
Build from scratch | Very High | Total | Very Slow | Very High |
Generate with Stainless or other tools | Low | High | Very Fast | Low |
Combine generate and custom code | Medium | Total | Fast | Medium |
We will explore each of these paths to help you make the right decision for your team.
Build from scratch
Building an SDK from the ground up gives you total control over the final product, but it is a massive undertaking. This path requires significant investment in engineering hours and deep expertise in the nuances of multiple programming languages. You are responsible for everything from the core HTTP client to the authentication logic, error handling, and release process for every language you support.
This approach is only justified in rare cases, such as when your API uses a non-standard protocol or you need an extremely bespoke developer experience that cannot be achieved through generation. For most companies, the high cost and slow timeline make this path impractical.
Generate with Stainless
A modern approach is to generate your SDKs directly from an OpenAPI specification, though creating OpenAPI specs that accurately represent your API is the crucial first step. You provide your API spec to a generation platform, which instantly produces idiomatic, production-ready SDKs in multiple languages. These are pushed to staging repositories where you can review them.
This path dramatically reduces the initial development time from months to days. Advanced generators like the Stainless SDK generator also provide tools like an SDK Studio to see live previews of your changes, run diagnostics to improve your spec, and manage the entire release process through automated pull requests.
Combine generate and custom code
The most powerful approach for many teams is a hybrid model. You can generate the core SDK to handle all the boilerplate and then layer on custom business logic or helper methods.
This gives you the best of both worlds: the speed and low maintenance of generation, with the flexibility to add bespoke features. Modern generation platforms are designed for this, supporting custom code that persists through regenerated code and even helping to automatically resolve merge conflicts when the underlying API changes.
Which languages deserve SDK investment
You do not need to support every language from day one. A strategic, phased rollout is the most effective approach. You can prioritize which languages to invest in by looking at a few key signals.
User agent logs: If you have existing API traffic, analyze your server logs to see which languages and frameworks your users are already using.
Community norms: Look at what languages are popular in your target developer communities. For example, data science APIs should prioritize Python, while web development APIs need strong TypeScript and JavaScript support.
Ecosystem maturity: Prioritize languages with strong tooling and package management ecosystems, as this makes it easier for developers to adopt your SDK.
A common strategy is to start with a small set of Tier 1 languages, gather feedback, and then expand.
Tier 1: TypeScript/JavaScript and Python cover a massive portion of the developer landscape and are excellent starting points.
Tier 2: Go, Java/Kotlin, and Ruby are strong next choices for expanding your reach into backend and enterprise development.
Tier 3: Mobile languages like Swift and Kotlin, or more niche languages, can be added later based on specific customer demand.
Modern SDK platforms allow you to toggle which languages you generate from a central configuration file, making it easy to manage this staged rollout.
SDK maintenance without the burden
Maintaining SDKs can be a significant challenge. For every new endpoint you add (M) and every language you support (N), your maintenance work grows, creating an N × M explosion of complexity. Manually keeping every SDK in sync with a rapidly evolving API is a recipe for bugs and developer frustration.
Automation is the only scalable solution. A CI-driven workflow can completely handle this burden. When you push a change to your OpenAPI spec, the process should automatically trigger a new build, run diagnostics, and open a release pull request in each SDK repository.
This PR should contain a full changelog generated from your commit messages, with the correct semantic version bump already calculated. All you have to do is review and merge to publish the update to its corresponding package registry. This keeps your libraries in lock-step with your API without diverting focus from your core product.
Future-proofing SDKs for AI agents
The next frontier for APIs is enabling interaction with AI agents and Large Language Models (LLMs). The Model Context Protocol (MCP) is an open standard that defines how LLMs can discover and use external tools, like your API. By providing an MCP server, you make your API AI-ready.
Building an MCP server from scratch can be complex, but modern SDK platforms simplify converting API to MCP by generating one directly from your OpenAPI spec, often as a subpackage within your TypeScript SDK.
Advanced MCP servers can even handle complex scenarios like dynamically exposing tools to work around an LLM's context window limitations or transforming schemas to adapt to the capabilities of different AI clients, with valuable lessons learned from converting complex OpenAPI specs to MCP servers.
Frequently asked questions about SDK implementation
How much does each implementation path cost?
Building from scratch can cost hundreds of thousands in engineering salaries and opportunity cost, while using a generator is a fraction of that price. A hybrid approach falls in between.
When can an API safely skip SDKs?
You might skip an SDK if your API is for internal use only, if you only need to support a single language and can provide a simple client library, or if it is a GraphQL API where client codegen is standard.
How do we measure SDK ROI?
Measure SDK return on investment through adoption metrics like downloads, improved time-to-first-call for new users, a reduction in API error rates, and a decrease in related support tickets.
What timeline should we expect for first release?
Building a single SDK from scratch can take months, while generating SDKs for multiple languages can be done in a matter of days. A hybrid approach typically takes a few weeks.
Should we open source our SDKs?
Open-sourcing your SDKs builds trust and allows for community contributions, but it also comes with the responsibility of managing issues, pull requests, and security reviews.