Ansible▌
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!
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
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
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.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 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
4.6★★★★★32 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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