Building Durable AI Applications with Temporal

Last updated on Jan 7, 2026

Learn how to build durable MCP (Model Context Protocol) tools using Temporal Workflows for reliable AI integrations.

• Tutorial 1: Build a weather forecast MCP server that Claude Desktop can use to fetch real-time weather data from the National Weather Service API. You'll implement the tool using Temporal Workflows, which handle the API calls, retries, and state management automatically.

• Tutorial 2: Add durable human-in-the-loop capabilities to a long-running invoice processing MCP tool with Temporal.

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📄️ Part 1: Creating a Durable Weather MCP Server with Temporal

Learn how to combine MCP (Model Context Protocol) and Temporal to build AI applications with powerful, durable tool integrations that automatically handle failures and retries.

📄️ Part 2: Building Long-Running MCP Tools with Human-in-the-Loop

Learn how to build long-running MCP tools with Temporal's signals and queries to implement human-in-the-loop patterns that can wait for human approval while maintaining durability.