developer-tools

Ansible

Knuckles-Team

by Knuckles-Team

Empower automation using Ansible Tower MCP Server—AI-ready, Docker support, and seamless orchestration for advanced work

Empower your automation workflows with an AI-ready interface for Ansible Tower. Ansible Tower MCP Server provides a versatile Model Context Protocol API for managing inventories, hosts, job templates, projects, credentials, users, teams, and workflows through AWX. With comprehensive resource coverage, Docker support, and environment-based configuration, it enables seamless integration with AI agents or programmatic tools. The server is actively maintained and designed for easy extension, making it a robust choice for both standalone service and advanced orchestration scenarios. Contributions are welcome to help drive cloud automation forward!

github stars

2

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Docker support includedEnvironment-based configurationComprehensive AWX API coverage

best for

  • / DevOps engineers automating infrastructure management
  • / AI agents controlling Ansible deployments
  • / Teams integrating Tower with custom automation tools

capabilities

  • / Manage Ansible Tower inventories and hosts
  • / Control job templates and workflow execution
  • / Configure projects and credentials
  • / Administer users, teams, and organizations
  • / Execute ad hoc Ansible commands
  • / Monitor automation job status

what it does

Provides an AI-ready interface to Ansible Tower/AWX for managing automation resources like inventories, job templates, projects, and workflows. Enables programmatic control of Ansible Tower through a standardized API.

about

Ansible is a community-built MCP server published by Knuckles-Team that provides AI assistants with tools and capabilities via the Model Context Protocol. Empower automation using Ansible Tower MCP Server—AI-ready, Docker support, and seamless orchestration for advanced work It is categorized under developer tools.

how to install

You can install Ansible in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Ansible is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Ansible Tower API - A2A | AG-UI | MCP

PyPI - Version MCP Server PyPI - Downloads GitHub Repo stars GitHub forks GitHub contributors PyPI - License GitHub

GitHub last commit (by committer) GitHub pull requests GitHub closed pull requests GitHub issues

GitHub top language GitHub language count GitHub repo size GitHub repo file count (file type) PyPI - Wheel PyPI - Implementation

Version: 1.3.32

Overview

The Ansible Tower MCP Server provides a Model Context Protocol (MCP) interface to interact with the Ansible Tower (AWX) API, enabling automation and management of Ansible Tower resources such as inventories, hosts, groups, job templates, projects, credentials, organizations, teams, users, ad hoc commands, workflow templates, workflow jobs, schedules, and system information. This server is designed to integrate seamlessly with AI-driven workflows and can be deployed as a standalone service or used programmatically.

This repository is actively maintained - This is a fork of a37ai/ansible-tower-mcp, which had not been updated in 6 months.

Contributions are welcome!

Features

  • Comprehensive API Coverage: Manage Ansible Tower resources including inventories, hosts, groups, job templates, projects, credentials, organizations, teams, users, ad hoc commands, workflows, and schedules.
  • MCP Integration: Exposes Ansible Tower API functionalities as MCP tools for use with AI agents or direct API calls.
  • Flexible Authentication: Supports both username/password and token-based authentication.
  • Environment Variable Support: Securely configure credentials and settings via environment variables.
  • Docker Support: Easily deployable as a Docker container for scalable environments.
  • Extensive Documentation: Clear examples and instructions for setup, usage, and testing.

MCP

MCP Tools

The ansible-tower-mcp package exposes the following MCP tools, organized by category:

Inventory Management

  • list_inventories(limit, offset): List all inventories.
  • get_inventory(inventory_id): Get details of a specific inventory.
  • create_inventory(name, organization_id, description): Create a new inventory.
  • update_inventory(inventory_id, name, description): Update an existing inventory.
  • delete_inventory(inventory_id): Delete an inventory.

Host Management

  • list_hosts(inventory_id, limit, offset): List hosts, optionally filtered by inventory.
  • get_host(host_id): Get details of a specific host.
  • create_host(name, inventory_id, variables, description): Create a new host.
  • update_host(host_id, name, variables, description): Update an existing host.
  • delete_host(host_id): Delete a host.

Group Management

  • list_groups(inventory_id, limit, offset): List groups in an inventory.
  • get_group(group_id): Get details of a specific group.
  • create_group(name, inventory_id, variables, description): Create a new group.
  • update_group(group_id, name, variables, description): Update an existing group.
  • delete_group(group_id): Delete a group.
  • add_host_to_group(group_id, host_id): Add a host to a group.
  • remove_host_from_group(group_id, host_id): Remove a host from a group.

Job Template Management

  • list_job_templates(limit, offset): List all job templates.
  • get_job_template(template_id): Get details of a specific job template.
  • create_job_template(name, inventory_id, project_id, playbook, credential_id, description, extra_vars): Create a new job template.
  • update_job_template(template_id, name, inventory_id, playbook, description, extra_vars): Update an existing job template.
  • delete_job_template(template_id): Delete a job template.
  • launch_job(template_id, extra_vars): Launch a job from a template.

Job Management

  • list_jobs(status, limit, offset): List jobs, optionally filtered by status.
  • get_job(job_id): Get details of a specific job.
  • cancel_job(job_id): Cancel a running job.
  • get_job_events(job_id, limit, offset): Get events for a job.
  • get_job_stdout(job_id, format): Get the output of a job in specified format (txt, html, json, ansi).

Project Management

  • list_projects(limit, offset): List all projects.
  • get_project(project_id): Get details of a specific project.
  • create_project(name, organization_id, scm_type, scm_url, scm_branch, credential_id, description): Create a new project.
  • update_project(project_id, name, scm_type, scm_url, scm_branch, description): Update an existing project.
  • delete_project(project_id): Delete a project.
  • sync_project(project_id): Sync a project with its SCM.

Credential Management

  • list_credentials(limit, offset): List all credentials.
  • get_credential(credential_id): Get details of a specific credential.
  • list_credential_types(limit, offset): List all credential types.
  • create_credential(name, credential_type_id, organization_id, inputs, description): Create a new credential.
  • update_credential(credential_id, name, inputs, description): Update an existing credential.
  • delete_credential(credential_id): Delete a credential.

Organization Management

  • list_organizations(limit, offset): List all organizations.
  • get_organization(organization_id): Get details of a specific organization.
  • create_organization(name, description): Create a new organization.
  • update_organization(organization_id, name, description): Update an existing organization.
  • delete_organization(organization_id): Delete an organization.

Team Management

  • list_teams(organization_id, limit, offset): List teams, optionally filtered by organization.
  • get_team(team_id): Get details of a specific team.
  • create_team(name, organization_id, description): Create a new team.
  • update_team(team_id, name, description): Update an existing team.
  • delete_team(team_id): Delete a team.

User Management

  • list_users(limit, offset): List all users.
  • get_user(user_id): Get details of a specific user.
  • create_user(username, password, first_name, last_name, email, is_superuser, is_system_auditor): Create a new user.
  • update_user(user_id, username, password, first_name, last_name, email, is_superuser, is_system_auditor): Update an existing user.
  • delete_user(user_id): Delete a user.

Ad Hoc Commands

  • run_ad_hoc_command(inventory_id, credential_id, module_name, module_args, limit, verbosity): Run an ad hoc command.
  • get_ad_hoc_command(command_id): Get details of an ad hoc command.
  • cancel_ad_hoc_command(command_id): Cancel an ad hoc command.

Workflow Templates

  • list_workflow_templates(limit, offset): List all workflow templates.
  • get_workflow_template(template_id): Get details of a specific workflow template.
  • launch_workflow(template_id, extra_vars): Launch a workflow from a template.

Workflow Jobs

  • list_workflow_jobs(status, limit, offset): List workflow jobs, optionally filtered by status.
  • get_workflow_job(job_id): Get details of a specific workflow job.
  • cancel_workflow_job(job_id): Cancel a running workflow job.

Schedule Management

  • list_schedules(unified_job_template_id, limit, offset): List schedules, optionally filtered by job/workflow template.
  • get_schedule(schedule_id): Get details of a specific schedule.
  • create_schedule(name, unified_job_template_id, rrule, description, extra_data): Create a new schedule.
  • update_schedule(schedule_id, name, rrule, description, extra_data): Update an existing schedule.
  • delete_schedule(schedule_id): Delete a schedule.

System Information

  • get_ansible_version(): Get the Ansible Tower version.
  • get_dashboard_stats(): Get dashboard statistics.
  • get_metrics(): Get system metrics.

A2A Agent

Architecture:

---
config:
  layout: dagre
---
flowchart TB
 subgraph subGraph0["Agent Capabilities"]
        C["Agent"]
        B["A2A Server - Uvicorn/FastAPI"]
        D["MCP Tools"]
        F["Agent Skills"]
  end
    C --> D & F
    A["User Query"] --> B
    B --> C
    D --> E["Platform API"]

     C:::agent
     B:::server
     A:::server
    classDef server fill:#f9f,stroke:#333
    classDef agent fill:#bbf,stroke:#333,stroke-width:2px
    style B stroke:#000000,fill:#FFD600
    style D stroke:#000000,fill:#BBDEFB
    style F fill:#BBDEFB
    style A fill:#C8E6C9
    style subGraph0 fill:#FFF9C4

Component Interaction Diagram

sequenceDiagram
    participant User
    participant Server as A2A Server
    participant Agent as Agent
    participant Skill as Agent Skills
    participant MCP as MCP Tools

    User->>Server: Send Query
    Server->>Agent: Invoke Agent
    Agent->>Skill: Analyze Skills Available
    Skill->>Agent: Provide Guidance on Next 

---

FAQ

What is the Ansible MCP server?
Ansible is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Ansible?
This profile displays 32 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.632 reviews
  • Liam Jackson· Dec 24, 2024

    Useful MCP listing: Ansible is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Ava Mehta· Nov 15, 2024

    According to our notes, Ansible benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Nia Sharma· Oct 6, 2024

    We wired Ansible into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Hiroshi Johnson· Sep 25, 2024

    Useful MCP listing: Ansible is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Yash Thakker· Sep 21, 2024

    According to our notes, Ansible benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Hiroshi Malhotra· Aug 16, 2024

    Ansible is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Dhruvi Jain· Aug 12, 2024

    We wired Ansible into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Layla Brown· Jul 27, 2024

    We evaluated Ansible against two servers with overlapping tools; this profile had the clearer scope statement.

  • Sakura Srinivasan· Jul 7, 2024

    We wired Ansible into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Oshnikdeep· Jul 3, 2024

    Ansible is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

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