Driving Innovation with the SmartBear MCP Hackathon
At SmartBear, innovation is not a side project. It is a mindset. In October, we hosted our first Model Context Protocol (MCP) Hackathon. An internal initiative designed to ignite creativity and hands-on experimentation across our global engineering teams.
We released our SmartBear MCP Server earlier this year, giving teams a practical foundation for experimenting with AI-driven workflows and exploring how large language models can interact directly with established development and testing tools. The hackathon was designed to push those boundaries, turning the protocol into a shared playground for engineers across our products.
The goal was to accelerate innovation around the MCP ecosystem, challenging teams to prototype cross-product workflows and developer utilities that demonstrate how MCP can enhance productivity and interoperability.
Collaboration Across Products and Regions
Engineers from SmartBear offices across the US, Europe, Australia, and India formed multidisciplinary teams drawn from Swagger, BugSnag, PactFlow, QMetry, and other product lines, collaborating globally to explore how MCP could connect and extend our tools in new ways. With just half a day to deliver working prototypes, teams used vibe coding techniques and AI tools such as GitHub Copilot, Claude, Gemini, and ChatGPT to brainstorm, generate, and refine ideas at record speed.
Initiatives like this hackathon are key to maintaining agility and fostering technical depth. They give engineers space to learn through creation, validate new concepts, and turn experimentation into tangible innovation, This isn’t just about pushing creation-velocity; it’s about moving up the autonomy ladder together – where coding, testing, observability and collaboration all level up in sync. By doing this, we close the gap between “I can build it” and “I trust what I’ve built,” empowering our teams to innovate boldly and deliver reliably.
Standout Projects
Among the standout projects was API Drift, an MCP server tool that automatically detects and resolves discrepancies between live API implementations, Swagger documentation, and PactFlow contracts. The idea came from a challenge every engineering team faces, keeping documentation and contract tests synchronized with rapidly evolving APIs.
The team behind API Drift built an MCP-powered workflow capable of running a single prompt to automate the entire reconciliation process:
“Use the Detect API Drift MCP tool to check my APIs. If you discover undocumented APIs: update the OpenAPI document locally, publish an updated version to SwaggerHub, and regenerate PactFlow tests where needed.”
By analyzing live production traffic from BugSnag, Swagger specs, and PactFlow contracts, the system could automatically identify outdated or missing endpoints, update documentation, increment versioning, and regenerate relevant PactFlow tests. In effect, the project demonstrated a self-healing documentation ecosystem with a glimpse into how MCP can automate consistency across connected SmartBear tools.
Another highlight was Quality Lens, a QA intelligence assistant designed to unify data from Jira, QMetry, and BugSnag into a single, actionable view of product quality. QA teams often struggle to see the full picture. Jira shows what is being built, QMetry tracks what is tested, and BugSnag reveals what is failing in production. The team’s goal was to eliminate this fragmentation.
Their MCP-driven workflow responded to a simple command:
“Analyze my Jira backlog, test coverage, and production errors, then generate a daily prioritized QA action plan that shows where we have risk, where tests are missing, and what we should work on next.”
The system correlated data across tools and produced a daily HTML-based report highlighting test coverage gaps, production errors, and a prioritized list of QA actions. The result was a single, trusted view of risk and quality, helping QA and engineering teams focus on what matters most while minimizing manual triage and context switching.
Both projects exemplified how SmartBear engineers used the MCP Server to turn disconnected workflows into autonomous, intelligent systems in just a few hours of experimentation.
Join the Developer Community
Want to explore what our teams built or start experimenting with MCP yourself? Join the SmartBear Community, where we will share project demos, code samples, and technical deep dives from the hackathon.
The community is open to all developers exploring MCP integrations, AI-driven tooling, and cross-product automation. Connect with SmartBear engineers, exchange ideas, and help shape the next generation of intelligent developer experiences.
Let us build the future of software autonomy together!