Connects Claude to live Helm chart repositories so it can query actual values.yaml schemas instead of guessing at field names. Exposes five tools: search charts by keyword, list available versions, fetch values with optional JSON path filtering and schema validation, inspect dependencies, and retrieve post-install notes. Works with both HTTP and OCI registries, though OCI requires knowing the chart name upfront since those registries don't support browsing. Useful when you're configuring Kubernetes deployments and need accurate chart documentation without leaving your editor. Ships as a Docker container or standalone binary, supports stdio and HTTP transports, and includes a public rate-limited instance at helm-mcp.kubedoll.com if you want to try it before self-hosting.
Give your AI assistant access to real Helm chart data. No more hallucinated values.yaml files.
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:
With mcp-helm:
mcp-helm implements the Model Context Protocol (MCP) — a standard way for AI assistants to access external data sources.
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?"
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"
}
}
}
| Tool | What it does | Useful parameters |
|---|---|---|
search_charts | List or search charts in a Helm repo | keyword (substring filter), limit |
get_versions | Get available versions of a chart (newest first) | limit=1 for the latest only |
get_values | Get chart values.yaml, optionally as a focused subsection | path (e.g. .ingress), depth (default 2, 0 for full YAML), include_schema=true, include_examples=true (requires path) |
get_dependencies | Get a chart's sub-charts (with their repo URLs, which can be fed back into the other tools) | — |
get_notes | Get chart NOTES.txt (post-install instructions) | — |
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.
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
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.
MIT — see LICENSE.
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