Skip to main content
Glama
AlexW00

ArtifactHub MCP Server

by AlexW00

ArtifactHub MCP Server

This is a Model Context Protocol (MCP) server for interacting with Helm charts on Artifacthub.

Usage

For VS-Code, click this auto-install-link.

Alternatively, use this MCP configuration:

{
	"servers": {
		"artifacthub-mcp": {
			"type": "stdio",
			"command": "docker",
			"args": ["run", "-i", "--rm", "ghcr.io/alexw00/artifacthub-mcp"]
		}
	}
}

Related MCP server: Prometheus MCP Server

Available tools

  • helm-chart-info: get information about a Helm chart such as id and latest version

  • helm-chart-values: get the default values.yaml of a Helm chart

  • helm-chart-values-fuzzy-search: fuzzy search for a value in the default values.yaml of a Helm chart

  • helm-chart-template: get a template of a Helm chart by name

  • helm-chart-template-fuzzy-search: fuzzy search the names/contents of templates

Available Tools

5 tools
helm-chart-infoB

Get information about a Helm chart from Artifact Hub, including ID, latest version, and description

ParametersJSON Schema
NameRequiredDescriptionDefault
chartRepoYesThe Helm chart repository name
chartNameYesThe Helm chart name

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states what information is returned. It doesn't disclose behavioral aspects like rate limits, authentication requirements, error conditions, pagination, or response format. The description is minimal beyond stating the basic operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with zero waste - every word contributes to understanding the tool's purpose. Front-loaded with the core action and resource, followed by source and specific return details. Appropriately sized for this simple tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations and no output schema, the description is too minimal. It doesn't explain what format the information comes in, whether it's a single object or list, error handling, or any limitations. The description should provide more context given the lack of structured metadata.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters adequately. The description doesn't add any parameter-specific context beyond what's in the schema descriptions. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get information'), resource ('Helm chart'), source ('from Artifact Hub'), and specific information included ('ID, latest version, and description'). It distinguishes from siblings by focusing on general chart metadata rather than templates or values.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when needing basic chart metadata from Artifact Hub, but doesn't explicitly state when to use this tool versus alternatives like the fuzzy-search siblings or template/value-specific tools. No explicit exclusions or comparison to siblings are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

helm-chart-templateC

Get the content of a template file from a Helm chart in Artifact Hub

ParametersJSON Schema
NameRequiredDescriptionDefault
chartRepoYesThe Helm chart repository name
chartNameYesThe Helm chart name
filenameYesExact filename (full path) to filter templates by (case-sensitive)
versionNoThe chart version (optional, defaults to latest)

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves content but doesn't mention whether it's a read-only operation, potential rate limits, authentication needs, or error handling. This leaves significant behavioral gaps for a tool interacting with an external service like Artifact Hub.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and efficiently conveys the core functionality, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of interacting with Helm charts and Artifact Hub, the description is insufficient. With no annotations, no output schema, and a tool that likely returns file content, it lacks details on response format, error cases, or dependencies. This leaves the agent with incomplete operational context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any additional meaning or context beyond what's in the schema, such as examples or usage notes. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get the content') and resource ('a template file from a Helm chart in Artifact Hub'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'helm-chart-templates-fuzzy-search' (which likely searches rather than retrieves exact content), so it misses full sibling distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'helm-chart-templates-fuzzy-search' for fuzzy matching or 'helm-chart-info' for general chart metadata, leaving the agent without context for tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

helm-chart-valuesC

Get the values.yaml file for a specific Helm chart from Artifact Hub

ParametersJSON Schema
NameRequiredDescriptionDefault
chartRepoYesThe Helm chart repository name
chartNameYesThe Helm chart name
versionNoThe chart version (optional, defaults to latest)

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states what the tool does but doesn't cover important aspects like authentication requirements, rate limits, error conditions, or what happens when the chart/version isn't found. For a read operation with external dependencies, this is inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a simple retrieval tool and front-loads the essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what format the values.yaml is returned in (raw text, parsed structure?), doesn't mention error scenarios, and provides no context about Artifact Hub integration. For a tool interacting with external systems, more completeness is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds no parameter semantics beyond what's already in the schema (which has 100% coverage). It doesn't explain the relationship between chartRepo and chartName, provide examples of valid values, or clarify what 'Artifact Hub' means in this context. Baseline 3 is appropriate since the schema does the documentation work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get') and resource ('values.yaml file for a specific Helm chart from Artifact Hub'), making the purpose immediately understandable. However, it doesn't explicitly distinguish this tool from its sibling 'helm-chart-values-fuzzy-search', which likely serves a similar purpose with different search behavior.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus its siblings. It doesn't mention alternatives like 'helm-chart-values-fuzzy-search' for approximate matching or 'helm-chart-info' for general metadata, leaving the agent without context for tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

TDQS

A3.5/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: helm-chart-info retrieves metadata, helm-chart-template gets specific template files, helm-chart-templates-fuzzy-search searches across templates, helm-chart-values retrieves the values.yaml file, and helm-chart-values-fuzzy-search searches within values.yaml. The descriptions make it unambiguous which tool to use for each task.

Naming Consistency5/5

All tools follow a consistent snake_case pattern with a clear 'helm-chart-' prefix and descriptive suffixes (-info, -template, -templates-fuzzy-search, -values, -values-fuzzy-search). This predictable naming convention makes it easy to understand each tool's function at a glance.

Tool Count5/5

With 5 tools, this server is well-scoped for its purpose of interacting with Helm charts on Artifact Hub. Each tool earns its place by covering distinct aspects: metadata retrieval, template access, values file access, and search capabilities for both templates and values.

Completeness4/5

The tool surface provides excellent coverage for querying and searching Helm chart components, but lacks any write operations (e.g., uploading or modifying charts). Given Artifact Hub's nature as a repository, this is reasonable, but agents cannot perform any creation or update actions through this interface.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

  • A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…

  • The Cortex MCP server provides read-only access to real-time engineering context from the Cortex developer portal, allowing AI coding assistants to answer natural language questions about your organization's catalog (microservices, libraries, domains, teams, infrastructure), scorecards (engineering standards and best practices), initiatives (goals and deadlines), and Engineering Intelligence metrics. It includes tools for querying documentation, tracking personal entities, and accessing AI-assisted insights across the entire Cortex ecosystem.

  • The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.

  • A Model Context Protocol server for Wix AI tools

Related MCP Servers

  • A
    license
    Not graded
    quality
    D
    maintenance
    A Model Context Protocol server that enables AI assistants to interact with Kubernetes clusters through natural language, supporting core Kubernetes operations, monitoring, security, and diagnostics.
    94
    956
    MIT
  • A
    license
    B
    quality
    F
    maintenance
    A Model Context Protocol server that enables AI assistants to query Prometheus metrics, discover available data, and analyze system performance through natural language interactions.
    5
    85
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    A Model Context Protocol server that provides tools for introspecting and analyzing FastAPI applications, including route discovery, model schema extraction, and source code viewing. It enables users to explore API structures, generate documentation, and debug dependency injection hierarchies through natural language.
    MIT

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AlexW00/artifacthub-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server