AWX

Provides an MCP server that connects AWX/Ansible Automation with AI tooling to manage templates, jobs, inventories, and projects.
  • python

0

GitHub Stars

python

Language

2 months ago

First Indexed

3 weeks ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs
{
  "mcpServers": {
    "surgex-labs-awx-mcp-server": {
      "command": "awx-mcp-server",
      "args": [
        "start",
        "--host",
        "0.0.0.0",
        "--port",
        "8000"
      ]
    }
  }
}

You can run the AWX MCP Server to connect AWX/Ansible Automation with AI tools, enabling natural language control over job templates, launches, inventories, and projects. This MCP server acts as a bridge that lets AI assistants manage AWX automation workflows through familiar MCP interfaces.

How to use

Set up the MCP server locally and connect your MCP client (such as an AI assistant or IDE integration) to manage AWX resources through natural language.

How to install

Prerequisites you need before installation.

# 1) Install and prepare the server (from the AWX MCP Python package)
# Note: Run these steps in a development environment or wherever you manage Python packages.
pip install -e .

# 2) Configure AWX environment interactively (if applicable in your setup)
# You will be guided to set up environments and credentials for AWX
awx-mcp-server env list

# 3) Start the MCP server (stdio transport, local server)
awx-mcp-server start --host 0.0.0.0 --port 8000

Additional sections

Security, deployment, and usage notes help you operate the MCP server safely and reliably.

Security

The server provides environment isolation and access control. Use HTTPS in production and manage secrets via environment variables where available.

Deployment options

You can run the server locally via stdio or deploy it in containerized environments. The standalone Python server supports local execution and can be paired with monitoring and orchestration stacks as needed.

Monitoring and debugging

Monitor requests and performance with built-in metrics endpoints and optional Prometheus/Grafana integrations when you deploy the server in production.

Notes

When you start the server, you should expose the required host and port values so your MCP clients can connect. If your AWX instance requires credentials, configure them in the AWX environment setup steps.

Available tools

env_list

List all configured AWX environments.

env_test

Test connection to the configured AWX environment.

env_get_active

Get the currently active AWX environment.

list_job_templates

List all AWX job templates, with optional filtering.

get_job_template

Get details for a specific job template by name or ID.

list_jobs

List all AWX jobs with optional filters by status or date.

get_job

Get details for a specific job by ID.

job_launch

Launch a job from a specified template with optional extra variables.

job_cancel

Cancel a running job.

job_stdout

Retrieve the standard output of a completed or running job.

job_events

Get events for a given job (playbook tasks and outcomes).

list_projects

List all AWX projects.

project_update

Update a project from source control.

list_inventories

List all AWX inventories.

get_inventory

Get details for a specific inventory.

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