MCP Argo Server

what is MCP Argo Server? MCP Argo Server is an MCP-compliant server designed for running Argo Workflows, implemented in Golang. It provides a lightweight CLI tool that wraps Argo Workflows using JSON-RPC over STDIN/STDOUT. how to use MCP Argo Server? To use MCP Argo Server, open the project in a development container or clone the repository and run go mod tidy. Use make cluster to install the k3d cluster and set up Argo, then submit a test workflow using argo submit -n argo --watch ./kube/argo-hello-world.yaml. key features of MCP Argo Server? Lightweight CLI tool for Argo Workflows JSON-RPC over STDIN/STDOUT for communication Integration with Kubernetes and Argo Workflow resources Python test client for workflow interaction use cases of MCP Argo Server? Launching and managing Argo Workflows in Kubernetes Monitoring workflow status and retrieving results Testing workflow submissions using a Python client FAQ from MCP Argo Server? Is MCP Argo Server easy to set up? Yes! It can be set up quickly using a development container or by running a few commands locally. Can I contribute to the project? Absolutely! Contributions are welcome, and you can submit issues and pull requests.

As an MCP (Model Context Protocol) server, MCP Argo Server enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

To use MCP Argo Server, open the project in a development container or clone the repository and run go mod tidy. Use make cluster to install the k3d cluster and set up Argo, then submit a test workflow using argo submit -n argo --watch ./kube/argo-hello-world.yaml. key features of MCP Argo Server? Lightweight CLI tool for Argo Workflows JSON-RPC over STDIN/STDOUT for communication Integration with Kubernetes and Argo Workflow resources Python test client for workflow interaction use cases of MCP Argo Server? Launching and managing Argo Workflows in Kubernetes Monitoring workflow status and retrieving results Testing workflow submissions using a Python client FAQ from MCP Argo Server? Is MCP Argo Server easy to set up? Yes! It can be set up quickly using a development container or by running a few commands locally. Can I contribute to the project? Absolutely! Contributions are welcome, and you can submit issues and pull requests.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.