Join Mumshad Mannambeth as he introduces the Model Context Protocol (MCP) and how it transforms DevOps & QA automation.
Discover how MCP enables reusable, secure, and tool-agnostic automation by standardizing how clients like IDEs, test runners, and AI assistants interact with server capabilities.
Learn to implement an MCP server for automated test environment provisioning, replacing brittle manual scripts with scalable, shareable workflows.
Walk away with a ready-to-adapt MCP server template and the confidence to bring MCP into your DevOps and testing pipelines.
Don’t miss out, book your free spot now
What strategies ensure automated test environments can scale dynamically to support multiple QA and DevOps teams in parallel?
How does adopting MCP help unify infrastructure, test data, and CI/CD workflows for better QA efficiency?
How can IaC tools like Terraform or CloudFormation be used to automate the provisioning and de-provisioning of diverse test environments for different stages of the CI/CD pipeline?
How does an agent differ from a chatbot?
As the complexity of modern apps grows, how can test data management and test environment automation be integrated to make sure that the right test data is available in the right environment at the right time?
What strategies can be implemented to enable developers and QA engineers to provision and manage their own on-demand test environments?
What techniques and considerations are key for optimizing the cost of maintaining and operating automated test environments (especially in cloud-based infrastructures)?
What are the common challenges encountered when attempting to automate test environments for legacy systems/app, and what strategies can be used to overcome them?
How does a test architecture using MCP compare to a traditional Page Object Model (POM)? Do they replace each other, or can they be used together effectively?
Many teams already use Jenkins, GitHub Actions, or GitLab for provisioning. What’s the practical first step to plug MCP into these pipelines without rewriting everything from scratch?
What are the architectural considerations for building an MCP server that can handle requests from a large number of clients (e.g., an entire QA department and CI/CD pipeline) simultaneously?
What is your take on AI impacting the SRE and DevOps engineers, how should one upskill to stay relevant in the market?
What advantage does MCP provide in terms of reusability across teams?
What role does MCP play in enabling shift-left testing in modern DevOps practices?
What’s the fastest win teams can get with MCP?
Is automating environments harder than automating tests themselves?
How do I introduce AI for our testing sessions within the team? How can I use AI effectively to handle our testings as well?
If an LLM responds with up-to-date information, how can you verify whether it is from its memory (training data) or from live retrieval?
What are the practical tips to apply MCP Servers for Mobile CI applications?
