Hoverfly Cloud AI for intelligent, AI driven API simulation

Hoverfly Cloud is now powered by AI

One of the many advantages of Hoverfly Cloud has always been its intuitive, easy-to-use interface. We’ve built a reputation for simplifying complex API simulations, freeing up developers to focus on what matters most: innovation.

So, how do you make what’s already a fantastic solution even better? We asked our community of dedicated users if there was one thing that could take their workflow to the next level. The overwhelming response? A desire for an even faster, more intuitive way to interact with the platform.

And now, we’ve taken Hoverfly a step further with a new feature that is set to transform your workflow: Hoverfly Cloud AI.

Meet Hoverfly Cloud AI: Your natural language new AI agent integration

Imagine configuring a complex API simulation simply by articulating a request in a chat window with a prompt for your AI agent. No more navigating menus or writing boilerplate scripts.

Our new feature lets you interact with Hoverfly Cloud using plain, natural language. This isn’t just a simple command line; it’s an intelligent AI assistant that understands your intent. Your AI agent translates requests into precise actions, making it easier than ever to get the exact simulation you need, exactly when you need it. Whether you’re a seasoned developer or new to the platform, this new approach simplifies everything.

A new standard: Hoverfly is transforming API simulation with AI

The AI functionality is the engine behind this new feature. It’s designed to allow you to safely and effectively control the different components of the Hoverfly Cloud platform, fundamentally changing how you work with APIs.

Hoverfly Cloud AI provides intelligent API simulation capabilities through Model Context Protocol (MCP), enabling your AI agent to create mock APIs directly from your development environment.

You can simply tell the AI what you want to achieve, and it handles the heavy lifting, such as:

• Creating and managing simulations with simple commands like, “Create a simulation for a new user registration API. ”
• Modifying existing simulations on the fly. You can instantly add a delay to a specific endpoint just by saying, “Add a 500ms delay to the login API.”
• Getting real-time feedback on the status of your APIs and simulations. You can simply ask your AI agent, “What's the status of my billing API?” and get an instant, clear response.
• Troubleshooting and debugging issues without navigating complex interfaces. The AI can help pinpoint problems, such as, “Why is the checkout API failing?” and provide insights based on the simulation data.

Real-world impact: How Hoverfly Cloud AI accelerates your workflow

Here are just some examples of how Hoverfly Cloud’s AI integration will transform your daily development and testing processes:

Use case 1: Creating and deploying API Simulations to replace the real ones in your software project

Setting up simulations for an existing software project can be time-consuming. Now, you can point the AI at your code and use natural language to create and deploy simulations that precisely mirror your current dependencies.

This detailed scenario illustrates the power of combining your project context with the intelligence of an LLM (Large Language Model):

• Open the chat in the context of a software code project that is already consuming real APIs.
• Ask your AI agent to build out a set of Hoverfly simulations that match the APIs that the project is already using.
• Instruct the AI to add configuration to the project to allow easy switching between the real and simulated APIs.
• Ask your AI agent to deploy the Hoverfly simulations and start services running on them.
• Change the project’s configuration to point to the new simulated APIs and run a test demonstration.
• Ask your AI agent to modify the APIs and deploy them so that they use CSV data to return realistic results.
• Ask your AI agent to modify the behaviour of one of the APIs so that it returns a specific error.

This workflow saves hours on manual configuration, allowing you to rapidly test error handling and real-world data scenarios without ever touching the real external service.

Use case 2: Generating simulations from API specifications

If you’re using API specification formats like OpenAPI (Swagger) or Postman collections, the AI can once again significantly accelerate your setup process. Instead of manually translating complex contracts into simulation scripts, you can prompt your AI agent to intelligently interpret these documents. This capability means you can bypass the tedious, error-prone manual work and immediately generate a reliable, contract-compliant mock service.

• Provide your AI agent with the OpenAPI (Swagger) or Postman collection.
• Ask your AI agent to create and deploy a full suite of simulations based on the specification, including realistic request and response bodies for every endpoint.
• Instantly deploy a fully-fledged mock service that precisely matches your API contract, allowing frontend and backend teams to start work immediately, in parallel.

Use case 3: Smart provisioning for test environments

Managing multiple test environments with different data sets and failure conditions can be a logistical nightmare. Different testing phases – from unit tests to User Acceptance Testing (UAT) –often require unique API behaviours and data.

With Hoverfly Cloud, you can once again prompt your AI agent to simplify your provisioning and turn a complex setup into a simple text command. By using a well-thought-out folder structure to organise your core assets, you gain fine-grained control over your test ecosystem:

• Organise your Hoverfly templates and associated test data (for example, in CSVs) using a clear folder structure.
• Prompt the AI to analyse your folder structure and understand the relationships between your templates and data.
• Ask your AI agent to launch a specific group of services for a particular test scenario, such as, “Launch the ‘VIP Customer’ environment with the successful payment scenario.”
• The AI will provision the correct simulations and data from the specified folders, ensuring a tailored, repeatable environment.
• After your testing is complete, you can then instruct the AI to tear down those groups of services immediately.

This approach simplifies the complexity of environment management, ensuring every team member can provision clean, repeatable testing environments based on the required test scenarios, all with a single, natural language command.

Use case 4: Document your API simulation assets

Good documentation is a must-have, but it’s often the first thing to be overlooked when you’re up against a tight deadline. Manual documentation is tedious and quickly falls out of sync with your working code.

With Hoverfly Cloud’s AI, you can now effortlessly turn your running simulations into useful, up-to-date assets for existing and new team members to reference. This ensures clarity and consistency across your development lifecycle:

• Prompt the AI with a simple instruction, such as “Document all currently running API simulation assets.”
• The AI will generate clear, concise documentation, detailing the endpoints, expected responses, failure modes, and data dependencies for each simulation.
• This ensures your simulation assets are easily understandable and maintainable for your whole team, acting as a living, up-to-date contract for your application’s external dependencies.

Elevate your API simulation workflow

These are just a few examples of how Hoverfly Cloud’s new AI-controlled functionality transforms complex configuration into simple, natural language tasks. By eliminating manual effort and injecting intelligence into your simulation process, you can accelerate your development, improve testing coverage, and bring new team members up to speed faster than ever before.

To see how Hoverfly Cloud AI can elevate your API simulation workflow, book a personalised demo today, and experience the advantage of intelligent API simulation.