MKP - Model Kontext Protocol Server for Kubernetes

MKP is a Model Context Protocol (MCP) server for Kubernetes that allows LLM-powered applications to interact with Kubernetes clusters. It provides tools for listing and applying Kubernetes resources through the MCP protocol.

Features

• List resources supported by the Kubernetes API server
• List clustered resources
• List namespaced resources
• Get resources and their subresources (including status, scale, logs, etc.)
• Apply (create or update) clustered resources
• Apply (create or update) namespaced resources
• Execute commands in pods with timeout control
• Generic and pluggable implementation using API Machinery's unstructured client
• Built-in rate limiting for protection against excessive API calls

Why MKP?

MKP offers several key advantages as a Model Context Protocol server for Kubernetes:

Native Go Implementation

• Built with the same language as Kubernetes itself
• Excellent performance characteristics for server applications
• Strong type safety and concurrency support
• Seamless integration with Kubernetes libraries

Direct API Integration

• Uses Kubernetes API machinery directly without external dependencies
• No reliance on kubectl, helm, or other CLI tools
• Communicates directly with the Kubernetes API server
• Reduced overhead and improved reliability

Universal Resource Support

• Works with any Kubernetes resource type through the unstructured client
• No hardcoded resource schemas or specialized handlers needed
• Automatically supports Custom Resource Definitions (CRDs)
• Future-proof for new Kubernetes resources

Minimalist Design

• Focused on core Kubernetes resource operations
• Clean, maintainable codebase with clear separation of concerns
• Lightweight with minimal dependencies
• Easy to understand, extend, and contribute to

Production-Ready Architecture

• Designed for reliability and performance in production environments
• Proper error handling and resource management
• Built-in rate limiting to protect against excessive API calls
• Testable design with comprehensive unit tests
• Follows Kubernetes development best practices

Prerequisites

• Go 1.24 or later
• Kubernetes cluster and kubeconfig
• Task for running tasks

Installation

1. Clone the repository:

   git clone https://github.com/StacklokLabs/mkp.git
   cd mkp
   

2. Install dependencies:

   task install
   

3. Build the server:

   task build
   

Usage

Running the server

To run the server with the default kubeconfig:

task run

To run the server with a specific kubeconfig:

KUBECONFIG=/path/to/kubeconfig task run-with-kubeconfig

To run the server on a specific port:

MCP_PORT=9091 task run

MCP Tools

The MKP server provides the following MCP tools:

get_resource

Get a Kubernetes resource or its subresource.

Parameters:

• resource_type (required): Type of resource to get (clustered or namespaced)
• group: API group (e.g., apps, networking.k8s.io)
• version (required): API version (e.g., v1, v1beta1)
• resource (required): Resource name (e.g., deployments, services)
• namespace: Namespace (required for namespaced resources)
• name (required): Name of the resource to get
• subresource: Subresource to get (e.g., status, scale, logs)
• parameters: Optional parameters for the request (see examples below)

Example:

{
  "name": "get_resource",
  "arguments": {
    "resource_type": "namespaced",
    "group": "apps",
    "version": "v1",
    "resource": "deployments",
    "namespace": "default",
    "name": "nginx-deployment",
    "subresource": "status"
  }
}

Example of getting logs from a specific container with parameters:

{
  "name": "get_resource",
  "arguments": {
    "resource_type": "namespaced",
    "group": "",
    "version": "v1",
    "resource": "pods",
    "namespace": "default",
    "name": "my-pod",
    "subresource": "logs",
    "parameters": {
      "container": "my-container",
      "sinceSeconds": "3600",
      "timestamps": "true",
      "limitBytes": "102400"
    }
  }
}

Available parameters for pod logs:

• container: Specify which container to get logs from
• previous: Get logs from previous container instance (true/false)
• sinceSeconds: Only return logs newer than a relative duration in seconds
• sinceTime: Only return logs after a specific time (RFC3339 format)
• timestamps: Include timestamps on each line (true/false)
• limitBytes: Maximum number of bytes to return
• tailLines: Number of lines to return from the end of the logs

By default, pod logs are limited to the last 100 lines and 32KB to avoid overwhelming the LLM's context window. These defaults can be overridden using the parameters above.

Available parameters for regular resources:

• resourceVersion: When specified, shows the resource at that particular version

list_resources

Lists Kubernetes resources of a specific type.

Parameters:

• resource_type (required): Type of resource to list (clustered or namespaced)
• group: API group (e.g., apps, networking.k8s.io)
• version (required): API version (e.g., v1, v1beta1)
• resource (required): Resource name (e.g., deployments, services)
• namespace: Namespace (required for namespaced resources)

Example:

{
  "name": "list_resources",
  "arguments": {
    "resource_type": "namespaced",
    "group": "apps",
    "version": "v1",
    "resource": "deployments",
    "namespace": "default"
  }
}

apply_resource

Applies (creates or updates) a Kubernetes resource.

Parameters:

• resource_type (required): Type of resource to apply (clustered or namespaced)
• group: API group (e.g., apps, networking.k8s.io)
• version (required): API version (e.g., v1, v1beta1)
• resource (required): Resource name (e.g., deployments, services)
• namespace: Namespace (required for namespaced resources)
• manifest (required): Resource manifest

Example:

{
  "name": "apply_resource",
  "arguments": {
    "resource_type": "namespaced",
    "group": "apps",
    "version": "v1",
    "resource": "deployments",
    "namespace": "default",
    "manifest": {
      "apiVersion": "apps/v1",
      "kind": "Deployment",
      "metadata": {
        "name": "nginx-deployment",
        "namespace": "default"
      },
      "spec": {
        "replicas": 3,
        "selector": {
          "matchLabels": {
            "app": "nginx"
          }
        },
        "template": {
          "metadata": {
            "labels": {
              "app": "nginx"
            }
          },
          "spec": {
            "containers": [
              {
                "name": "nginx",
                "image": "nginx:latest",
                "ports": [
                  {
                    "containerPort": 80
                  }
                ]
              }
            ]
          }
        }
      }
    }
  }
}

post_resource

Posts to a Kubernetes resource or its subresource, particularly useful for executing commands in pods.

Parameters:

• resource_type (required): Type of resource to post to (clustered or namespaced)
• group: API group (e.g., apps, networking.k8s.io)
• version (required): API version (e.g., v1, v1beta1)
• resource (required): Resource name (e.g., deployments, services)
• namespace: Namespace (required for namespaced resources)
• name (required): Name of the resource to post to
• subresource: Subresource to post to (e.g., exec)
• body (required): Body to post to the resource
• parameters: Optional parameters for the request

Example of executing a command in a pod:

{
  "name": "post_resource",
  "arguments": {
    "resource_type": "namespaced",
    "group": "",
    "version": "v1",
    "resource": "pods",
    "namespace": "default",
    "name": "my-pod",
    "subresource": "exec",
    "body": {
      "command": ["ls", "-la", "/"],
      "container": "my-container",
      "timeout": 30
    }
  }
}

The body for pod exec supports the following fields:

• command (required): Command to execute, either as a string or an array of strings
• container (optional): Container name to execute the command in (defaults to the first container)
• timeout (optional): Timeout in seconds (defaults to 15 seconds, maximum 60 seconds)

Note on timeouts:

• Default timeout: 15 seconds if not specified
• Maximum timeout: 60 seconds (any larger value will be capped)
• Commands that exceed the timeout will be terminated and return a timeout error

The response includes stdout, stderr, and any error message:

{
  "apiVersion": "v1",
  "kind": "Pod",
  "metadata": {
    "name": "my-pod",
    "namespace": "default"
  },
  "spec": {
    "command": ["ls", "-la", "/"]
  },
  "status": {
    "stdout": "total 48\ndrwxr-xr-x   1 root root 4096 May  5 14:30 .\ndrwxr-xr-x   1 root root 4096 May  5 14:30 ..\n...",
    "stderr": "",
    "error": ""
  }
}

MCP Resources

The MKP server provides access to Kubernetes resources through MCP resources. The resource URIs follow these formats:

• Clustered resources: k8s://clustered/{group}/{version}/{resource}/{name}
• Namespaced resources: k8s://namespaced/{namespace}/{group}/{version}/{resource}/{name}

Configuration

Controlling Resource Discovery

By default, MKP serves all Kubernetes resources as MCP resources, which provides useful context for LLMs. However, in large clusters with many resources, this can consume significant context space in the LLM.

You can disable this behavior by using the --serve-resources flag:

# Run without serving cluster resources
./build/mkp-server --serve-resources=false

# Run with a specific kubeconfig without serving cluster resources
./build/mkp-server --kubeconfig=/path/to/kubeconfig --serve-resources=false

Even with resource discovery disabled, the MCP tools (get_resource, list_resources, apply_resource, delete_resource, and post_resource) remain fully functional, allowing you to interact with your Kubernetes cluster.

Enabling Write Operations

By default, MKP operates in read-only mode, meaning it does not allow write operations on the cluster, i.e. the apply_resource, delete_resource, and post_resource tools will not be available. You can enable write operations by using the --read-write flag:

# Run with write operations enabled
./build/mkp-server --read-write=true

# Run with a specific kubeconfig and write operations enabled
./build/mkp-server --kubeconfig=/path/to/kubeconfig --read-write=true

Rate Limiting

MKP includes a built-in rate limiting mechanism to protect the server from excessive API calls, which is particularly important when used with AI agents. The rate limiter uses a token bucket algorithm and applies different limits based on the operation type:

• Read operations (list_resources, get_resource): 120 requests per minute
• Write operations (apply_resource, delete_resource): 30 requests per minute
• Default for other operations: 60 requests per minute

Rate limits are applied per client session, ensuring fair resource allocation across multiple clients. The rate limiting feature can be enabled or disabled via the command line flag:

# Run with rate limiting enabled (default)
./build/mkp-server

# Run with rate limiting disabled
./build/mkp-server --enable-rate-limiting=false

Development

Running tests

task test

Formatting code

task fmt

Linting code

task lint

Updating dependencies

task deps

Running as an MCP Server with ToolHive

MKP can be run as a Model Context Protocol (MCP) server using ToolHive, which simplifies the deployment and management of MCP servers.

Prerequisites

1. Install ToolHive by following the installation instructions.
2. Ensure you have Docker or Podman installed on your system.
3. Configure your Kubernetes credentials (kubeconfig) for the cluster you want to interact with.

Running MKP with ToolHive (Recommended)

The easiest way to run MKP is using the packaged version available in ToolHive's registry:

# Register a supported client so ToolHive can auto-configure your environment
thv client setup

# Run the MKP server (packaged as 'k8s' in ToolHive)
# Mount your kubeconfig so the server can access your Kubernetes cluster
thv run --volume $HOME/.kube:/home/nonroot/.kube:ro k8s

# List running servers
thv list

# Get detailed information about the server
thv registry info k8s

This will mount your Kubernetes credentials and make the server available to your MCP-compatible clients.

Advanced Usage with Custom Configuration

For advanced users who need custom configuration, you can also run MKP using the container image directly:

# Run the MKP server using the published container image
thv run --name mkp --transport sse --target-port 8080 --volume $HOME/.kube:/home/nonroot/.kube:ro ghcr.io/stackloklabs/mkp/server:latest

This command:

• Names the server instance "mkp"
• Uses the SSE transport protocol
• Mounts your local kubeconfig into the container (read-only)
• Uses the latest published MKP image from GitHub Container Registry

To use a specific version instead of the latest:

thv run --name mkp --transport sse --target-port 8080 --volume $HOME/.kube:/home/nonroot/.kube:ro ghcr.io/stackloklabs/mkp/server:v0.0.1

Managing the MKP Server

To verify that the MKP server is running:

thv list

This will show all running MCP servers managed by ToolHive, including the MKP server.

To stop the MKP server:

# For packaged version
thv stop k8s

# For custom named version
thv stop mkp

To remove the server instance completely:

# For packaged version
thv rm k8s

# For custom named version
thv rm mkp

Contributing

We welcome contributions to this MCP server! If you'd like to contribute, please review the CONTRIBUTING guide for details on how to get started.

If you run into a bug or have a feature request, please open an issue in the repository or join us in the #mcp-servers channel on our community Discord server.

License

This project is licensed under the Apache v2 License - see the LICENSE file for details.