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    Mcp Cyclops

    Model Context Protocol server for Cyclops

    29 stars
    Go
    Updated Jun 25, 2025
    cyclops
    devops
    kubernetes
    mcp
    mcp-server
    platform-engineering

    Documentation

    Cyclops MCP (Model Context Protocol)

    Cyclops MCP allows your favorite AI agent to manage your Kubernetes applications. Cyclops MCP servers provide tools for agents to create and update existing applications safely.

    https://github.com/user-attachments/assets/0c675c33-1e36-4fdb-bf8c-2fd7fb491e6b

    This means it can check all of your existing templates and the schema of those templates to create accurate and production-ready applications. Your agent now has much less room to make a misconfiguration since it creates high-level resources (Cyclops Modules) instead of touching every line of your Kubernetes resources (Deployments, Services, and Ingresses).

    It allows you to move fast and ensure no uncaught misconfigurations are hitting your production.

    With Cyclops and our MCP, you can now abstract Kubernetes complexity from your developers AND your AI agents

    Install via UI

    The easiest way to install the Cyclops MCP server is through the Cyclops UI. Below are instructions on how to install it via binary and kubectl, but the recommended way of installing it is via the UI.

    ⚠️ To install Cyclops MCP through the UI, you should run Cyclops on a version v0.20.1 or greater

    1. Install the Cyclops MCP by going to sidebar “Addon” > "MCP server". You can now click "Install Cyclops MCP server" and your Cyclops MCP server will be up and running in a few seconds.

    2. Now that your MCP server is up running, all thats left is exposing it outside of your cluster and connecting your AI agent to it.

    To expose the MCP server on localhost you can simply port-forward it with the following command:

    bash
    kubectl port-forward -n cyclops svc/cyclops-mcp 8000:8000

    Your server is now available on localhost:8000.

    3. To connect it to an AI agent you will just have to provide the Cyclops MCP server in its configuration. For example, to add it to Cursor, you can simply add it with the following JSON:

    bash
    {
          "mcpServers": {
            "cyclops-kubernetes": {
              "url": "http://localhost:8000/sse"
            }
          }
        }

    You can now start a fresh conversation with your AI companion. Above is an example of how we used it with Cursor.

    Install stdin binary

    1. Make sure Cyclops is installed in your Kubernetes cluster

    Check our docs on how it install it with a single command - https://cyclops-ui.com/docs/installation/install/manifest

    2. Download MCP server

    You can download the Cyclops MCP server binary with the following command:

    yaml
    GOBIN="$HOME/go/bin" go install github.com/cyclops-ui/mcp-cyclops/cmd/mcp-cyclops@latest

    3. Add server configuration

    ⚠️ By default, Cyclops MCP will use the .kube/config file to connect to your cluster

    Configure your MCP Cyclops server:

    json
    {
      "mcpServers": {
        "mcp-cyclops": {
          "command": "mcp-cyclops"
        }
      }
    }

    Configuration

    You can configure Cyclops MCP server via env variables. Below is an example of adding the configuration for specifying the kubeconfig file the Cyclops MCP server should use when managing your Cyclops applications.

    json
    {
      "mcpServers": {
        "mcp-cyclops": {
          "command": "mcp-cyclops",
          "env": {
            "KUBECONFIG": "/path/to/your/kubeconfig"
          }
        }
      }
    }

    Environment variables

    Below is the list of environment variables used for configuring your Cyclops MCP server:

    Env varDescription
    KUBECONFIGPath to kubeconfig file (optional, defaults to in-cluster config or $HOME/.kube/config)
    CYCLOPS_KUBE_CONTEXTKubernetes context to use (optional)
    CYCLOPS_MODULE_NAMESPACENamespace where modules are stored
    CYCLOPS_HELM_RELEASE_NAMESPACENamespace for Helm releases
    CYCLOPS_MODULE_TARGET_NAMESPACETarget namespace for modules

    ---

    Install to a Kubernetes cluster manually

    ---

    Instead of having each developer install mcp-cyclops binary, you can install the Cyclops MCP server with SSE as transport type to your Kubernetes cluster and allow all of your developers to connect to the same server.

    1. Before installing, make sure Cyclops and all its CRDs are installed in your cluster:

    1. Check Cyclops pods are running:

    shell
    kubectl get pods -n cyclops

    Should write:

    code
    NAME                            READY   STATUS    RESTARTS   AGE
            cyclops-ctrl-676b5d9789-ntcls   1/1     Running   0          94s
            cyclops-ui-7798655f97-xdg29     1/1     Running   0          94s

    2. Check if CRDs are installed

    shell
    kubectl get crds | grep cyclops-ui

    Should write:

    code
    modules.cyclops-ui.com             2025-04-26T15:28:18Z
            templateauthrules.cyclops-ui.com   2025-04-26T15:28:18Z
            templatestores.cyclops-ui.com      2025-04-26T15:28:18Z

    2. Install Cyclops MCP server with the following command:

    shell
    kubectl apply -f https://raw.githubusercontent.com/cyclops-ui/mcp-cyclops/refs/heads/main/install/mcp-server.yaml

    3. You can now expose the cyclops-mcp service. To test your MCP server, you can port-forward it:

    shell
    kubectl port-forward svc/cyclops-mcp -n cyclops 8000:8000

    4. Add your Cyclops MCP server host, or in case you are testing it, the localhost address where you port-forwarded the MCP service:

    json
    {
          "mcpServers": {
            "mcp-cyclops": {
              "url": "http://localhost:8000/sse"
            }
          }
        }

    ---

    Tools

    ToolDescription
    create_moduleCreate new Module. Before calling this tool, make sure to call get_template_schema to validate values for the given template
    get_moduleFetch Module by name
    list_modulesList all Cyclops Modules
    update_moduleUpdate Module by Name. Before calling this tool, make sure to call get_template_schema to validate values for the given template
    get_template_schemaReturns JSON schema for the given template. Needs to be checked before calling create_module tool
    get_template_storeFetch Template Store by Name
    list_template_storeList Template Stores from cluster

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