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MCP Argo Server

by jakkaj

AI/Automation & Workflowargo workflowsjson-rpckubernetesgolangcli

MCP Argo Server is a lightweight CLI tool that wraps Argo Workflows using JSON-RPC over STDIN/STDOUT. It provides tools for launching workflows, checking workflow status, and retrieving results.

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MCP Argo Server

An MCP-compliant server for running Argo Workflows written in Golang.

Overview

MCP Argo Server is a lightweight CLI tool that wraps Argo Workflows using JSON-RPC over STDIN/STDOUT. It leverages Foxy Contexts for RPC handling and client-go for interacting with Kubernetes and Argo Workflow resources. The project provides tools for launching workflows, checking workflow status, and retrieving results.

Installation

This project is configured to run inside a development container. Simply open the repository in your dev container-enabled editor (e.g., VS Code Remote - Containers) and all dependencies are pre-installed.
If you prefer to run it locally, clone the repository and run:

go mod tidy

Usage

Open the project in the dev container.

Run make cluster which will install the k3d cluster and set up Argo.

You can check that's worked by typing kubectl cluster-info.

You can run a test workflow by typing argo submit -n argo --watch ./kube/argo-hello-world.yaml.

You can see the Argo interface at https://localhost:2746/workflows/argo/

You can check that the app is building and the MCP is working by typing make run.

Testing with Python

The project includes a Python test client that demonstrates how to interact with the MCP Argo server. The test client is located in python/test_with_autogen.py and showcases:

  • Submitting Argo workflows
  • Checking workflow status
  • Waiting for workflow completion
  • Retrieving workflow results

To run the Python test:

  1. Ensure you have Python dependencies installed:

    cd python
make install

  2. Run the test script:

    python test_with_autogen.py

or... just debug it to step through.

The script will:

  • Connect to the MCP Argo server
  • Iterate the tools and print them out
  • Submit a sample workflow from kube/argo-hello-world.yaml
  • Monitor the workflow status until completion
  • Display the workflow results

Contributing

Contributions are welcome! Please open issues and submit pull requests. Before submitting changes, ensure that you follow the project's coding guidelines and that all tests pass.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Additional Resources