"Basic Image Editing Operations like Resizing, Cropping, and Blurring" matching MCP servers:

Enables querying Azure VM image-baking pipeline runs, build status, and release evidence, and safely queueing pipeline runs with strict confirmation and parameter allow-lists.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

Provides AI assistants with access to Capawesome documentation and Cloud management tools, enabling app, build, and deployment operations via API token authentication.

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.

Analyzes database migrations for risks like lock contention and data loss before they run. Supports Flyway and Liquibase formats, providing risk scores and rollback generation.

MCP server exposing Apache Airflow REST API operations as tools — list DAGs, inspect runs and task instances, trigger DAG runs, and check failed DAGs and scheduler health

MCP server for Argo CD and Vault that allows authenticated users to run CLI commands via GitLab SSO, with confirmation for dangerous operations and secret redaction from model context.

Governed CI/CD operations for self-hosted GitLab and Gitea — pipeline-failure, runner, artifact-bloat, and stale-branch RCA, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

Enables inspection and management of Apache Airflow DAGs, runs, and logs across multiple instances. It provides tools for monitoring workflows and performing gated write operations like triggering DAGs or clearing task instances.

Enables comprehensive GitLab integration allowing LLMs to manage projects, issues, merge requests, repository files, CI/CD pipelines, and perform batch operations. Supports advanced features like AI-optimized summaries, smart diffs, and atomic operations with rollback support.

Enables AI assistants to manage CData Sync operations, including data synchronization jobs, connections, and ETL processes through stdio or HTTP transports. It provides tools for executing jobs, monitoring real-time progress via Server-Sent Events, and handling comprehensive workspace configurations.

A Model Context Protocol (MCP) server for LocalStack that enables management of local AWS development environments, including container lifecycle operations, infrastructure deployments, log analysis with IAM policy generation, chaos injection, and Cloud Pods state management.

Python MCP server for GitHub operations, providing native tool integration with Claude Code and other MCP clients. It enables managing issues, pull requests, CI status, milestones, and batch operations via natural language.

Enables AI assistants to interact with Azure DevOps Server 2022 through natural language, enabling queries and operations on pipelines, pull requests, builds, and repositories.

Enables management of Railway.app infrastructure through natural language, allowing users to deploy services, manage environment variables, monitor deployments, and configure projects directly from MCP clients like Claude.

MCP server exposing the Laravel Forge API v2 with curated tools for deploys, logs, env, and services plus universal access to all 273 operations.

Enables checking project files like Dockerfile, .nvmrc, and CI workflows to determine whether pinned runtime, database, and OS versions are still supported, providing end-of-life dates, latest patches, and upgrade targets for 470+ products.

Safety-first GitOps operations for ArgoCD via the Model Context Protocol. Enables listing, diagnosing, syncing, and managing ArgoCD applications with progressive disclosure and defense-in-depth security.

Enables monitoring and debugging of Hatchet workflows and jobs through MCP clients like Claude Code. Users can list workflows, track run statuses, query queue metrics, and retrieve job results using natural language commands.

Enables creation and management of Terraform modules for Facets.cloud infrastructure with interactive generation, validation, forking, testing, and deployment workflows through secure file operations and FTF CLI integration.