he purpose of this repo is to demonstrate how easy it is to leverage workflows as tools for MCP servers by taking modelcontext.io's weather example and making it durable by implementing the MCP tools as Temporal workflows
Overview
What is Temporal Durable MCP Weather Sample?
Temporal Durable MCP Weather Sample is a project that demonstrates how to leverage workflows as tools for MCP servers by enhancing modelcontext.io's weather example with durability through Temporal workflows.
How to use Temporal Durable MCP Weather Sample?
To use this project, clone the repository, set up a virtual environment, install the necessary dependencies, start the Temporal server and worker, and configure Claude for Desktop to utilize the weather tools.
Key features of Temporal Durable MCP Weather Sample?
- Demonstrates the implementation of MCP tools as Temporal workflows.
- Provides a durable solution for handling weather data.
- Integrates with Claude for Desktop for weather alerts and forecasts.
Use cases of Temporal Durable MCP Weather Sample?
- Managing weather alerts and forecasts through a conversational interface.
- Demonstrating the durability of workflows in complex operations.
- Enhancing MCP server capabilities with Temporal workflows.
FAQ from Temporal Durable MCP Weather Sample?
- What are the prerequisites for using this project?
You need Python3+, uv, and a local setup of Temporal.
- How does this project improve upon traditional MCP implementations?
It adds durability and state management to workflows, allowing for recovery from interruptions without losing progress.