"Headroom open-notebook resources" matching MCP servers:

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.

An MCP server that lets AI assistants manage KubeAid GitOps clusters, inspecting ArgoCD apps, pods, events, and resources, with optional write operations like syncing apps and scaling deployments through your own kubeconfig credentials.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.

Baron gives an AI coding agent one normalized contract for work orchestration: create and transition issues, cut branches, open and merge pull requests, and read CI and deployment status across Azure DevOps, GitHub and Slack.

An MCP server that drives Google Play releases: bundle upload, track releases (internal/closed/open/production), listing metadata, store graphics, and review replies.

Enables AI assistants to deploy and manage SnapDeploy containers and resources—including builds, logs, environment variables, databases, and custom domains—directly through natural language.

Enables management of Railway.app infrastructure through natural language, including deploying services, managing environment variables, monitoring deployments, and controlling project resources.

An MCP (Model Context Protocol) server that integrates with the ArgoCD API, enabling AI assistants and large language models to manage ArgoCD applications and resources through natural language interactions.

Enables real-time assessment of GitHub repository health by exposing tools and resources for repository metadata, open issues, recent commits, and GitHub Actions workflow runs, plus prompts for health reports and issue triage.

Checks the outcome after an agent handoff, when a request, 200 or ack only shows the handoff. Reads one field of one exact public HTTPS JSON record, with a same-site known-good control, for 20-120 s. Returns PROVED, DISPROVED or INCONCLUSIVE with a signed receipt you can verify. 5 free checks, then USD 1 per completed check, by card (Stripe Checkout) or existing Link wallet. INCONCLUSIVE is free.

LoopSense is an open-source MCP server that closes the feedback loop for AI coding agents — giving them real-time visibility into CI results, deployments, test outcomes, and file system changes.

Enables AI assistants to inspect, query, and diagnose problems within Octopus Deploy instances. Provides read-only access to deployments, releases, projects, environments, and other DevOps resources to transform AI into your ultimate DevOps wingmate.

Enables AI assistants to interact with Argo CD through its REST API, providing tools to triage application status, sync, roll back, inspect drift, read logs, and manage ApplicationSets, clusters, projects, and repositories. Supports read-only safeguards, curated GitOps resources, and workflow prompts for safe operations.

Connects AI tools directly to Codemend production error monitoring to list, analyze, and resolve software crashes. It enables users to retrieve AI-generated fixes and automatically open GitHub pull requests to address production issues.

Enterprise-grade MCP server exposing Ansible Automation Platform 2.x as a complete AI interface for LLMs, enabling natural language management of automation resources.

A Python MCP server that wraps the GitHub CLI (gh) to provide structured tools for searching, reading, and managing GitHub resources like repos, issues, PRs, releases, and workflows, with write commands disabled by default.

Enables AI agents to read repositories, manage issues, inspect CI/CD workflow runs, create branches, commit files, and open pull requests on a self-hosted Gitea instance.

The Model Context Protocol (MCP) Jenkins integration is an open-source implementation that bridges Jenkins with AI language models following Anthropic's MCP specification. This project enables secure, contextual AI interactions with Jenkins tools while maintaining data privacy and security.

MCP server for Laravel Cloud to manage projects, environments, deployments, and other resources.

Enables AI assistants to interact with and manage Google Cloud Platform resources including Artifact Registry, BigQuery, Cloud Build, Compute Engine, Cloud Run, Cloud Storage, and monitoring services through a standardized MCP interface.

A Model Context Protocol server that enables AI assistants to interact with Azure DevOps resources including projects, work items, repositories, pull requests, branches, and pipelines through a standardized protocol.

An MCP server for Infrastructure as Code that enables AI assistants to manage cloud resources through Ansible and Terraform operations. It supports executing playbooks, managing AWS services, and running Terraform commands with optional LocalStack integration.

Enables management of App Store Connect resources including app reviews, TestFlight crashes, analytics reports, and Xcode Cloud workflows through natural language or AI agents.

A Model Context Protocol server that provides tools and resources for Java CI/CD workflows and GitLab CI template management.

Enables programmatic management of Koyeb resources including apps, services, deployments, and instances via the Model Context Protocol. It allows users to query build and runtime logs and perform resource lifecycle operations through the Koyeb API.

Enables AI agents to create, deploy, and manage Netlify projects and resources using natural language via the Netlify API and CLI.

Provides complete control over Dokploy infrastructure with 463 tools for managing projects, applications, databases, and Docker containers. It enables users to deploy and configure their self-hosted PaaS resources directly through natural language.

MCP server plugin for the tsdevstack CLI, enabling AI agents to manage infrastructure, deployment, and project state with 54 tools and 12 resources.

Enables AI assistants to interact with Bitbucket repositories, pull requests, and related resources through the Bitbucket Cloud and Server APIs. It supports operations such as listing repositories, retrieving repository details, and fetching or creating pull requests.

Enables AI assistants to interact with Bitbucket Cloud and Server APIs, including listing and retrieving repositories, fetching pull requests, creating pull requests, and managing related resources safely without DELETE operations.