The Model Context Protocol is emerging as the de facto standard way for AI agents to interface with downstream services - microservices, data sources and more. While it’s designed to be used in LLM-centric applications, under the covers an MCP server ultimately implements calls to concrete APIs. APIs that can fail. APIs that might be unavailable due to network limitations. APIs that might be rate limited. Your AI applications and agents can only be as reliable as the MCP servers they leverage.
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Senior Staff Developer Advocate
Cornelia has spent a career at the forefront of technological innovation, starting with image processing algorithm development, moving to web-centric computing in the late 1990s, and then more than a decade working in cloud-native software and DevOps platforms. As a Developer Advocate for Temporal, she is now helping to drive the expansion of the “durable execution” distributed systems paradigm.
She is the author of Cloud Native Patterns: Designing change tolerant software.
Manager, Product Marketing
Temporal Technologies
Meagan is currently a Product Marketing Manager at Temporal Technologies bridging the gap between our technical teams and sales and marketing. Previously, Meagan was in product marketing at Cockroach Labs.