Awx MCP Server
A

Awx MCP Server

The AWX MCP Server is an industry-standard MCP server that connects the AWX/Ansible automation platform to AI tools, enabling AI assistants to manage job templates, start and monitor tasks, and manage inventories and projects using natural language, automating infrastructure workflows.
2 points
3.3K

What is the AWX MCP Server?

The AWX MCP Server is a bridge that connects AI assistants (such as GitHub Copilot, Claude, Cursor, etc.) to the AWX/AAP/Ansible Tower automation platform. It implements the Model Context Protocol (MCP) standard, allowing you to interact with the automation platform using natural language without having to memorize complex command lines or API calls.

How to use the AWX MCP Server?

You can choose between two main usage modes: 1) Integrate it directly into AI tools as an MCP server (recommended), or 2) Use it as an independent web server for the team. After installation, use natural language commands directly in the AI chat interface, such as 'List all job templates' or 'Start a deployment job'.

Use cases

Suitable for developers, operations teams, and automation engineers, especially those who want to: - Quickly perform AWX operations through AI assistants - Reduce the need to memorize complex commands - Share automation capabilities through team collaboration - Integrate AWX into chatbots or custom applications

Main features

Multi-platform support
Supports AWX (open-source version), Ansible Automation Platform (Red Hat version), and Ansible Tower (traditional version) simultaneously, using the same API interface.
18+ AWX operations
Supports a complete set of AWX operations, including job template management, job start and monitoring, project management, inventory management, etc.
Dual-mode deployment
Provides an MCP server mode (integrated into AI tools) and a web server mode (for team use) to meet different scenario requirements.
Natural language interaction
Control AWX using natural language through an AI assistant without having to memorize complex commands or API syntax.
Enterprise-level features
Supports multi-tenancy, API key authentication, monitoring metrics, containerized deployment, and Kubernetes integration.
VS Code extension
An optional VS Code extension provides a sidebar view, a tree resource browser, and a configuration interface to enhance the development experience.
Advantages
๐Ÿš€ Quick integration: Add AWX functionality to an AI assistant within minutes
๐ŸŽฏ User-friendly: Interact using natural language, reducing the usage threshold
๐Ÿ”Œ Wide compatibility: Supports all MCP-compatible tools (Copilot, Claude, Cursor, etc.)
๐Ÿข Enterprise-ready: Supports production features such as multi-tenancy, monitoring, and containerization
๐Ÿ”„ Flexible deployment: Provides two modes: a local MCP server and a remote web server
Limitations
๐Ÿ“š Requires basic configuration: AWX connection information needs to be configured for the first use
๐Ÿ” Security considerations: API keys and access permissions need to be properly managed in a production environment
โšก Network-dependent: Requires a stable network connection to the AWX instance
๐Ÿ› ๏ธ Technical stack: Basic Python and container knowledge is required for advanced deployment

How to use

Choose an installation method
Choose an installation method according to your needs: - Install from PyPI (recommended for a quick start) - Install from source code (for custom development) - Use a Docker container (for team deployment)
Configure the AWX connection
Set the URL and access token of the AWX instance. You can set them through environment variables or a configuration file.
Configure the AI tool
Add the MCP server configuration in the VS Code settings or configure other MCP-compatible tools.
Start using
Use the @awx command or directly ask AWX-related questions in the AI chat interface.

Usage examples

Quickly view available templates
New team members need to understand the available automation jobs and can quickly browse through an AI assistant.
One-click application deployment
Developers need to deploy code to a test environment and can trigger the deployment process using natural language commands.
Troubleshooting
Operations personnel need to view the detailed logs of failed jobs to troubleshoot problems.
Batch operations
Administrators need to update the source code of multiple projects.

Frequently Asked Questions

Which AI tools does the AWX MCP Server support?
Do I need professional knowledge of AWX?
How to ensure security?
Can I connect to multiple AWX instances simultaneously?
How can a team use this tool?
Are there monitoring and logging functions?

Related resources

Official GitHub repository
Source code, issue tracking, and contribution guidelines
PyPI package page
Python package releases and version history
Model Context Protocol documentation
Official specification and standards of the MCP protocol
AWX official documentation
Official documentation of the Ansible Automation Platform
Installation guide from source code
Detailed guide for custom development and installation from source code
Deployment architecture documentation
Detailed explanation of single-user vs. team/enterprise deployment options

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "awx": {
      "command": "python",
      "args": ["-m", "awx_mcp_server"],
      "env": {
        "AWX_BASE_URL": "https://your-awx.com"
      },
      "secrets": {
        "AWX_TOKEN": "your-awx-token"
      }
    }
  }
}

{
  "mcpServers": {
    "awx": {
      "command": "/path/to/awx-mcp-server/awx-mcp-python/server/venv/bin/python",
      "args": ["-m", "awx_mcp_server"],
      "env": {
        "AWX_BASE_URL": "https://your-awx.com"
      },
      "secrets": {
        "AWX_TOKEN": "your-token"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

V
Vestige
Vestige is an AI memory engine based on cognitive science. By implementing 29 neuroscience modules such as prediction error gating, FSRS - 6 spaced repetition, and memory dreaming, it provides long - term memory capabilities for AI. It includes a 3D visualization dashboard and 21 MCP tools, runs completely locally, and does not require the cloud.
Rust
4.6K
4.5 points
M
Moltbrain
MoltBrain is a long-term memory layer plugin designed for OpenClaw, MoltBook, and Claude Code, capable of automatically learning and recalling project context, providing intelligent search, observation recording, analysis statistics, and persistent storage functions.
TypeScript
5.2K
4.5 points
B
Bm.md
A feature-rich Markdown typesetting tool that supports multiple style themes and platform adaptation, providing real-time editing preview, image export, and API integration capabilities
TypeScript
3.8K
5 points
S
Security Detections MCP
Security Detections MCP is a server based on the Model Context Protocol that allows LLMs to query a unified security detection rule database covering Sigma, Splunk ESCU, Elastic, and KQL formats. The latest version 3.0 is upgraded to an autonomous detection engineering platform that can automatically extract TTPs from threat intelligence, analyze coverage gaps, generate SIEM-native format detection rules, run tests, and verify. The project includes over 71 tools, 11 pre-built workflow prompts, and a knowledge graph system, supporting multiple SIEM platforms.
TypeScript
5.1K
4 points
P
Paperbanana
Python
7.3K
5 points
B
Better Icons
An MCP server and CLI tool that provides search and retrieval of over 200,000 icons, supports more than 150 icon libraries, and helps AI assistants and developers quickly obtain and use icons.
TypeScript
5.9K
4.5 points
A
Assistant Ui
assistant - ui is an open - source TypeScript/React library for quickly building production - grade AI chat interfaces, providing composable UI components, streaming responses, accessibility, etc., and supporting multiple AI backends and models.
TypeScript
6.6K
5 points
A
Apify MCP Server
The Apify MCP Server is a tool based on the Model Context Protocol (MCP) that allows AI assistants to extract data from websites such as social media, search engines, and e-commerce through thousands of ready-to-use crawlers, scrapers, and automation tools (Apify Actors). It supports OAuth and Skyfire proxy payment and can be integrated into MCP clients such as Claude and VS Code through HTTPS endpoints or local stdio.
TypeScript
7.7K
5 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
20.4K
4.5 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
24.6K
4.3 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
35.5K
5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
73.1K
4.3 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
31.2K
5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
65.6K
4.5 points
G
Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
22.1K
4.5 points
M
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
48.0K
4.8 points