PurePerformance MCPs (Model Context Protocol) are not that magic, but they enable magic things with Dana Harrison
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Apr 14, 2025 Dana Harrison, a Staff Site Reliability Engineer at Telus, shares insights on Model Context Protocols (MCPs) and their transformative potential for engineers. He explains how MCPs enhance API interactions, streamlining data retrieval and increasing efficiency. The discussion touches on the critical differences between local and remote MCPs, resilience in API connections, and the importance of observing interactions for better management. With a focus on rapidly evolving software development, Dana sheds light on the exciting challenges and opportunities faced in the AI landscape.
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MCPs: A Universal Connector for AI
- MCPs (Model Context Protocol) are like USB-C for AI, a standard interface for LLMs to connect to external resources.
- They enable LLMs to interact with tools and data by parsing data received from them.
Example: Querying Chatter with MCPs
- Andy Grabner gives an example of querying organizational chatter on Slack and email using MCP servers.
- Dana Harrison explains how to build MCP servers for different platforms to gather and interpret data.
MCPs: Beyond Data Retrieval
- MCPs offer a standardized way for LLMs to interact with backend systems, avoiding point-to-point integrations.
- They handle data retrieval and actions based on how the MCP server is built.