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"Information about Ansible - IT automation tool" matching MCP servers:

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    Enables AI assistants to interact with Gitea repositories through intelligent tools for issue/PR management, workflow analysis, compliance checking, and content generation, plus 200+ CLI commands for complete CRUD operations.
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    MIT
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    Exposes open automation platform capabilities to AI agents with tools for managing job templates, inventories, collections, EDA activations, audit events, and policy checks, governed by gateway auth, RBAC, and policy enforcement.
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    Enables intelligent management of Google Cloud Platform infrastructure using Terragrunt, with support for experimental stacks, parallel deployments, resource visualization, cost analysis, and comprehensive infrastructure operations through natural language.
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    GPL 3.0
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    A multi-Jenkins server management and automation tool that enables intelligent scenario mapping, multi-server management, and complete CI/CD lifecycle operations through natural language interactions.
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    A feature-complete TypeScript project template for rapidly developing Model Context Protocol tools with integrated best practices for code quality, testing, and automated deployment.
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    Enterprise-grade MCP server exposing Ansible Automation Platform 2.x as a complete AI interface for LLMs, enabling natural language management of automation resources.
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    Apache 2.0
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    A curated MCP server for Semaphore UI that enables driving Ansible and Terraform automation from Claude with a safe, read-first tool surface.
    BSD 2-Clause "Simplified"
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    Industry-standard MCP server for AWX/AAP/Ansible Tower automation, enabling AI agents to manage job templates, launch and monitor jobs, and handle inventories and projects through natural language.
    10
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    Record an agent's MCP tool-call workflow once, replay it deterministically for zero tokens, and get a receipt — a snapshot-testing and deterministic-execution layer for Agent Skills.
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    An MCP server that enables AI assistants to discover and execute Nox sessions for project automation tasks like testing, linting, and building. It provides tools to list available sessions and run them using specific Python versions, tags, or keyword expressions.
    2
    MIT
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    Compacts noisy test, build, and cloud-log output before an AI agent reads it — dedupes repeats, collapses stack frames, folds Playwright retries, and renders CloudWatch/GCP JSON logs down to the signal. Typically 80–95% fewer tokens on failures. Tool: compact_output. Run: npx -y logslim logslim-mcp
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    MIT