The Model Context Protocol, or MCP, is a new open standard that connects AI assistants to arbitrary data sources and tools, such as codebases, APIs, and content repositories. Instead of building bespoke integrations for each system, developers can use MCP to establish secure, scalable connections between AI models and the data they need. By standardizing this connection layer, MCP enables models to access relevant information in real time, leading to more accurate and context-aware responses.
David Soria Parra is a Member of the Technical Staff at Anthropic, where he co-created the Model Context Protocol. He joins the podcast to talk about his career and the future of context-aware AI.
Jordi Mon Companys is a product manager and marketer that specializes in software delivery, developer experience, cloud native and open source. He has developed his career at companies like GitLab, Weaveworks, Harness and other platform and devtool providers. His interests range from software supply chain security to open source innovation. You can reach out to him on Twitter at @jordimonpmm
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Sponsors
This episode of Software Engineering Daily is brought to you by Capital One.
How does Capital One stack? It starts with applied research and leveraging data to build AI models. Their engineering teams use the power of the cloud and platform standardization and automation to embed AI solutions throughout the business. Real-time data at scale enables these proprietary AI solutions to help Capital One improve the financial lives of its customers. That’s technology at Capital One.
Learn more about how Capital One’s modern tech stack, data ecosystem, and application of AI/ML are central to the business by visiting www.capitalone.com/tech.
Developers, we’ve all been there… It’s 3 AM and your phone blares, jolting you awake. Another alert. You scramble to troubleshoot, but the complexity of your microservices environment makes it nearly impossible to pinpoint the problem quickly.
That’s why Chronosphere is on a mission to help you take back control with Differential Diagnosis, a new distributed tracing feature that takes the guesswork out of troubleshooting. With just one click, DDx automatically analyzes all spans and dimensions related to a service, pinpointing the most likely cause of the issue.
Don’t let troubleshooting drag you into the early hours of the morning. Just “DDx it” and resolve issues faster.
See why Chronosphere was named a leader in the 2024 Gartner Magic Quadrant for Observability Platforms at chronosphere.io/sed.
