mcp-helm

Give your AI assistant access to real Helm chart data. No more hallucinated values.yaml files.

What is this?

When you ask Claude, Cursor, or other AI assistants to help with Kubernetes deployments, they don't have access to Helm chart schemas. So they guess — and the guesses look plausible but don't match reality.

Without mcp-helm:

• :x: Hallucinates field names that look right but don't exist

• :x: Suggests stale or deprecated chart versions

• :x: Wastes tokens on web fetches and guesswork

With mcp-helm:

• :white_check_mark: Queries actual Helm repositories for real chart data

• :white_check_mark: Gets the latest chart version automatically

• :white_check_mark: Correct configurations the first time

mcp-helm implements the Model Context Protocol (MCP) — a standard way for AI assistants to access external data sources.

Related MCP server: ArtifactHub MCP Server

Try It Now

Add this to your editor's MCP config to use our public instance (rate limited, no install required):

{
  "mcpServers": {
    "helm": {
      "type": "http",
      "url": "https://helm-mcp.kubedoll.com/mcp"
    }
  }
}

Then ask your AI: "What values can I configure for the bitnami/postgresql chart?"

Editor Setup

Edit ~/.claude/mcp.json:

{
  "mcpServers": {
    "helm": {
      "command": "docker",
      "args": ["run", "--rm", "-i", "ghcr.io/kubedoll-heavy-industries/mcp-helm", "--transport=stdio"]
    }
  }
}

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "helm": {
      "command": "docker",
      "args": ["run", "--rm", "-i", "ghcr.io/kubedoll-heavy-industries/mcp-helm", "--transport=stdio"]
    }
  }
}

Edit MCP settings in Cursor's configuration:

{
  "mcpServers": {
    "helm": {
      "command": "docker",
      "args": ["run", "--rm", "-i", "ghcr.io/kubedoll-heavy-industries/mcp-helm", "--transport=stdio"]
    }
  }
}

Add to your Continue config (~/.continue/config.json):

{
  "experimental": {
    "modelContextProtocolServers": [
      {
        "transport": {
          "type": "stdio",
          "command": "docker",
          "args": ["run", "--rm", "-i", "ghcr.io/kubedoll-heavy-industries/mcp-helm", "--transport=stdio"]
        }
      }
    ]
  }
}

If you prefer to run the binary directly, install mcp-helm and replace the Docker config with:

{
  "mcpServers": {
    "helm": {
      "command": "mcp-helm"
    }
  }
}

Available Tools

OCI registries (oci://...) do not support browsing — for OCI you must already know the chart name, then call get_versions or get_values directly with that name.

Install

Docker (recommended — no install required, used in Editor Setup above):

docker pull ghcr.io/kubedoll-heavy-industries/mcp-helm:latest

Binary:

curl -fsSL https://github.com/kubedoll-heavy-industries/helm-mcp/releases/latest/download/mcp-helm_$(uname -s)_$(uname -m).tar.gz | tar xz
sudo mv mcp-helm /usr/local/bin/

Go:

go install github.com/kubedoll-heavy-industries/helm-mcp/cmd/mcp-helm@latest

Self-Hosting

For shared deployments or when you need an HTTP endpoint:

docker run -p 8012:8012 ghcr.io/kubedoll-heavy-industries/mcp-helm:latest \
  --transport=http --listen=:8012
# Connect to http://localhost:8012/mcp

See docs/self-hosting.md for health endpoints and production recommendations.

Documentation

• Configuration Reference — CLI flags, env vars, transport modes

• Self-Hosting Guide — Docker HTTP, health endpoints, production tips

• Troubleshooting — common issues and fixes

• Contributing — development setup, testing, PR guidelines

• Security Policy — reporting vulnerabilities

License

MIT — see LICENSE.