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PatternFly MCP Server

Organization
patternfly

An MCP server that provides access to PatternFly rules and documentation.

Publisherpatternfly
Repositorypatternfly-mcp
LanguageTypeScript
Forks
10
Stars
3
Available tools
3
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    PatternFly MCP Server exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 3 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    3 stars and 10 forks from the linked repository.

PatternFly MCP Server

A Model Context Protocol (MCP) server that provides access to PatternFly rules and documentation, built with Node.js.

The PatternFly MCP server is a comprehensive library resource for PatternFly. It is intended to be extensible to meet the needs of different teams and projects, from simple to complex, from design to development. Read more about our roadmap and how we've structured the server in our architecture docs.

Requirements

Quick start

The PatternFly MCP Server supports multiple configurations; see the usage documentation for details.

For integrated use with an IDE

Set a basic MCP configuration

Minimal configuration

json
{
  "mcpServers": {
    "patternfly-mcp": {
      "command": "npx",
      "args": ["-y", "@patternfly/patternfly-mcp@latest"],
      "description": "PatternFly rules and documentation"
    }
  }
}

HTTP transport mode

json
{
  "mcpServers": {
    "patternfly-mcp": {
      "command": "npx",
      "args": ["-y", "@patternfly/patternfly-mcp@latest", "--http", "--port", "8080"],
      "description": "PatternFly rules and documentation (HTTP transport)"
    }
  }
}

See the MCP Server Configuration documentation for more examples.

For development, advanced usage

Run the latest released server

Run the latest published package immediately via npx:

bash
npx -y @patternfly/patternfly-mcp@latest

Or with options

bash
npx -y @patternfly/patternfly-mcp@latest --log-stderr --verbose

Run a locally built server

bash
# clone the repo, change the directory, npm install, npm run build, then in the repo context run...
npm start

Inspect the server

Visualize and test the packaged MCP interface:

bash
npx -y @modelcontextprotocol/inspector npx -y @patternfly/patternfly-mcp@latest

Build from source and test a local built MCP interface:

bash
# clone the repo, change the directory, npm install, npm run build, then in the repo context run...
npx -y @modelcontextprotocol/inspector node dist/cli.js

Embed the server in your application

typescript
import { start } from '@patternfly/patternfly-mcp';

// Remember to avoid using console.log and info, they pollute STDOUT
async function main() {
  const server = await start();

  // Graceful shutdown
  process.on('SIGINT', async () => {
    await server.stop();
    process.exit(0);
  });
}

main();

See the development documentation for additional examples, CLI and embedded server options.

Documentation

For comprehensive usage, development, and project state read the docs.

Contributing

Contributing? Guidelines can be found here CONTRIBUTING.md.

AI agent

If you're using an AI assistant to help with development in this repository, please prompt it to review the repo guidelines to ensure adherence to project conventions.

Guidelines for developer-agent interaction can be found in CONTRIBUTING.md.

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "patternfly-docs": {
      "command": "npx",
      "args": [
        "-y",
        "@patternfly/patternfly-mcp@latest"
      ],
      "env": {}
    }
  }
}

Available Tools

  • usePatternFlyDocs

    Get markdown documentation and component JSON schemas for PatternFly components.

      **Usage**:
        1. Input a component name (e.g., "Button") OR a list of up to 15 documentation URLs at a time (typically from searchPatternFlyDocs results).
    
      **Returns**:
        - Markdown documentation
        - Component JSON schemas, if available
      
    
  • searchPatternFlyDocs

    Search PatternFly components and get component names with documentation URLs. Supports case-insensitive partial and all ("*") matches.

      **Usage**:
        1. Input a "searchQuery" to find PatternFly documentation URLs and component names.
        2. Use the returned component names OR URLs with the "usePatternFlyDocs" tool to get markdown documentation and component JSON schemas.
    
      **Returns**:
        - Component names that can be used with "usePatternFlyDocs"
        - Documentation URLs that can be used with "usePatternFlyDocs"
      
    
  • componentSchemas

    [Deprecated: Use "usePatternFlyDocs" to retrieve component schemas from PatternFly documentation URLs.]

      Get JSON Schema for a PatternFly React component.
    
      Returns prop definitions, types, and validation rules. Use this for structured component metadata, not documentation.
    

Use PatternFly MCP Server MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once PatternFly MCP Server is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add PatternFly MCP Server as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the PatternFly MCP Server MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "patternfly-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@patternfly/patternfly-mcp@latest"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the PatternFly MCP Server MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the PatternFly MCP Server MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use PatternFly MCP Server to help me with this task?
PatternFly MCP Server
Sure. I read it.
Here is what I found using PatternFly MCP Server.

Frequently asked questions

What is the PatternFly MCP Server MCP server used for?

PatternFly MCP Server is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use PatternFly MCP Server MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use PatternFly MCP Server with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use PatternFly MCP Server MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With PatternFly MCP Server connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect PatternFly MCP Server MCP to TypingMind?

PatternFly MCP Server runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does PatternFly MCP Server MCP provide in TypingMind?

PatternFly MCP Server exposes 3 MCP tools that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use PatternFly MCP Server MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If PatternFly MCP Server requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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