Updated on by Susanna Fagerholm
APIs are the connective tissue of modern software. They let products share data, trigger workflows, and support the kinds of automations customers expect as standard. Good API development means thinking beyond whether the API functions correctly in isolation.
An API that’s technically sound but difficult to integrate with will create friction for anyone that tries to connect to it. That friction has a habit of turning into an integration backlog and a development team drowning in integration requests with no clear way out.
At Cyclr, our expert team of connector developers spends a lot of time integrating with third-party APIs across a wide range of industries and architectures. Over time, the patterns that make APIs genuinely easy to build against and maintain have become clear.
Here are 8 best practices on API development that help teams stay focused on what matters, whether they’re building their first API or revisiting an existing design.
1. Get Authentication Right from the Start
Authentication is the front door to an API, and it needs to be solid. Especially now that AI agents are becoming a key user of SaaS, it is more important than ever to limit who can access what.
OAuth 2.0 Authorization Code flow is the most commonly used and generally preferred approach for multi-tenant SaaS APIs. It supports secure, redirect-based handshakes and works well in scenarios where tokens need to be stored and refreshed server-side. Other supported patterns include API keys (passed via HTTP header), Basic authentication, and OAuth 2.0 Client Credentials.
No matter which authentication model is chosen, integrations tend to go more smoothly when:
- Authentication rules are consistent across the API surface
- Token expiry and refresh behaviour is clearly defined
- Scopes follow least-privilege (only grant what is needed)
As AI agents become mainstream API consumers, SaaS teams are increasingly being asked whether their API is accessible via the Model Context Protocol (MCP). Authentication design is also the right starting point for teams thinking about how to make an API MCP-accessible, so that AI agents can interact with it as a structured tool.
2. Design Resources Around Nouns, Not Actions
Good API development means designing endpoints that are intuitive and predictable. Resource-oriented design, where endpoints represent things rather than actions, is the clearest way to achieve this.
In REST APIs, that means using standard HTTP verbs consistently:
- GET to read or retrieve a resource
- POST to create a resource
- PUT or PATCH to update a resource
- DELETE to remove a resource
Keep naming consistent, too. Pluralization, casing, and terminology should follow the same patterns throughout. Avoid embedding workflow logic or UI concepts into the API design. Consistency across the API surface is ultimately more important than any particular stylistic decision made along the way.
3. Build in Change Tracking
This one gets overlooked more than it should. For integrations that synchronize data between systems, change detection is critical. Without it, integrations often end up doing full data polls every time they run, which can quickly become slow and hard to maintain.
The fix is simple: every record should expose a created_at timestamp and an updated_at (or equivalent) timestamp. List and search endpoints should then support filtering on those fields. This gives anyone building an integration with the API the ability to efficiently retrieve only newly created records, or records that have changed since a given point in time.
This single design decision can reduce the need for custom scripting and make an API far easier to work with.
4. Always Paginate Collection Endpoints
If an API returns a list of records, it should be paginated. Even if initial data volumes are small, applying pagination to all list endpoints from the beginning is a much better approach than retrofitting it later when performance becomes an issue.
The good news is that most common pagination approaches work well. Page/size, offset/limit, and cursor-based pagination are all widely supported in integration platforms like Cyclr. What matters most is that the pagination behavior is clearly documented and deterministic, so developers know exactly what to expect from one request to the next.
It is also worth thinking about page size intentionally. Returning too much data in one call increases payload size, timeouts, and the chance of partial failures. Many APIs define practical defaults and enforce maximum page sizes to protect both the provider and the client.
5. Be Deliberate About What Data Is Returned
Returning everything available by default might seem like a helpful option, but it can create real performance problems. If a resource contains many properties, returning all of them with every request can be inefficient, especially on endpoints that return large collections.
Allowing API consumers to specify which fields they want returned reduces unnecessary payload size and improves performance. Even without a fully flexible field-selection mechanism, being intentional at the design stage about what each endpoint returns goes a long way.
6. Make Error Handling Consistent and Actionable
Nothing slows down API development and integration work quite like cryptic or inconsistent error responses. Good error handling means using appropriate HTTP status codes, returning structured and machine-readable error payloads, and writing error messages that are actually useful to the developers (or agents) consuming the API.
Crucially, the format of those error responses should be consistent across all endpoints. When error handling is reliable and predictable, it becomes much easier to build and maintain the logic that handles failures gracefully.
7. Treat Documentation as a First-Class Deliverable
Documentation quality has a direct impact on how quickly and reliably integrations can be built. Third-party developers are not familiar with an internal domain model or a team’s assumptions, so documentation needs to carry the full weight of that context.
At a minimum, good API documentation should include:
- Clear endpoint descriptions
- Authentication instructions
- Request and response payload schemas
- Example requests and responses
- Common error scenarios
Keeping documentation up to date as the API evolves is just as important as getting it right initially.
More on what makes great API documentation can be found in Cyclr’s guide on how to develop an API.
8. Plan for Stability and Change Management
Integrations are built on the assumption that APIs behave consistently over time. Even small, well-intentioned breaking changes can cascade into outages across multiple customer workflows. Teams can avoid a lot of headaches when they plan ahead for these changes in the API development stage.
Best practice here is to avoid breaking changes wherever possible. When they’re unavoidable, the API should be versioned, a meaningful deprecation window provided, and changes communicated clearly in advance. The cost of managing change poorly gets multiplied across every integration that relies on the API.
This is also where consistency pays off again. If the API is internally consistent, it can be evolved with additive changes more easily, and clients can adopt new capabilities without reworking existing flows.
Building APIs and Integration Strategies That Scale
The best API development combines technical correctness with genuine usability. Clear authentication, predictable resources, timestamps that enable synchronization, and documentation that gives developers what they need to get going quickly. These are the qualities that make an API worth integrating with, and the foundation for strategies to stop building one-off connectors for every customer.
But good API design only goes so far on its own. SaaS teams that are serious about scaling their integration capability without scaling their engineering headcount need more than a well-designed API. They need a connectivity strategy that meets customer demand without turning every new request into a development project.
That’s exactly what Cyclr is built to do. With a library of hundreds of pre-built connectors, an embedded integration platform that sits inside the SaaS product, and tooling that lets customers self-serve their own integrations, Cyclr gives development teams their time back and gives SaaS businesses a scalable path to the integrations that drive retention and growth.
If your team is thinking about customer-facing integrations, external data access, AI orchestration, or MCP delivery, this is the right time to look at them as one platform problem instead of four separate projects.
See how Cyclr helps B2B SaaS companies deliver interoperability natively, securely, and at scale.
Our integration experts can take you through the platform and answer any and all of your questions, just book a demo today!
