Continuous Integration and Continuous Deployment tools and workflows. Enables automation of software delivery pipelines, build processes, testing, and deployment operations.
This MCP server lets you use Cursor IDE, or any MCP Client enabled agent, to use natural language to accomplish things with CircleCI, e.g: Find the latest failed pipeline on my branch and get logs
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.
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.
A Model Context Protocol server that monitors shadow-cljs builds and provides real-time build status updates for ClojureScript projects, allowing LLMs to verify build status after making code changes.
A unified control center for managing MCP servers, providing tooling for environment variable management, profile-based configurations, and local package installation automation.
Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.
A Model Context Protocol server that enables AI assistants to interact with Azure DevOps services, allowing users to query work items with plans to support creating/updating items, managing pipelines, handling pull requests, and administering sprints and branch policies.
A Model Context Protocol server that enables interaction with GitLab accounts to manage repositories, merge requests, code reviews, and CI/CD pipelines through natural language.
A Model Context Protocol server that enables AI assistants to interact with Jenkins CI/CD servers, providing tools to check build statuses, trigger builds, and retrieve build logs.
A Model Context Protocol server that allows management of Netlify sites, enabling users to create, list, get information about, and delete Netlify sites directly from an MCP-enabled environment.
Facilitates unified execution and result parsing for various testing frameworks, including Bats, Pytest, Flutter, Jest, and Go, through a Model Context Protocol interface.
GitLab MCP Server (with activity tracking and group projects listing features)
This server is based on the original GitLab MCP server with Group Projects Listing and Activity Tracking enhancements
An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.
A Model Context Protocol server that enables integration with GitHub Actions, allowing users to fetch available actions, get detailed information about specific actions, trigger workflow dispatch events, and fetch repository releases.
An MCP server that executes tox commands to run Python tests within a project using pytest, allowing users to run all tests or specific test groups, files, cases, or directories.
An MCP server that enables AI assistants to manage GitHub Actions workflows by providing tools for listing, viewing, triggering, canceling, and rerunning workflows through the GitHub API.
A server interface for Bitrise CI/CD platform that enables app management, build operations, artifact management, and release management through natural language interactions.
A Model Context Protocol server that provides tools for interacting with Docker images, containers, and registries, enabling AI assistants to search, analyze, and manage Docker resources through a standardized interface.
A local MCP server that exposes Bazel build system functionality to AI agents, allowing them to build, test, query, and manage Bazel projects through natural language even in environments where Bazel can't be directly accessed.
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.
A Model Context Protocol (MCP) server that enables AI tools like chatbots to interact with and control Jenkins, allowing users to trigger jobs, check build statuses, and perform other Jenkins operations through natural language.
A Model Context Protocol server implementation that allows AI models to interact with and manage Spinnaker deployments, pipelines, and applications through a standardized interface.
A server that integrates with Stripe for handling payments, customers, and refunds through the Model Context Protocol, providing a secure API to manage financial transactions.
A Model Context Protocol server that enables automated end-to-end testing with LLMs using Playwright's accessibility tree rather than pixel-based inputs.
A Multi-Claude Program for interacting with GitHub APIs through Claude Desktop, allowing users to search repositories, manage issues, pull requests, repository settings, workflows, and collaborators.
Facilitates deployment and management of services using the Model Context Protocol with a focus on high availability, scalability, and secure communication, leveraging Docker-based infrastructure, Prometheus, and Grafana for monitoring.
A FastAPI-based JSON-RPC 2.0 server implementation that enables users to work with HDF5 files, submit Slurm jobs, retrieve CPU information, and visualize CSV data through standardized API endpoints.
A Model Context Protocol server that provides integration with the Coolify API, enabling DevOps teams to manage Coolify deployments, applications, services, and servers through MCP tools.
An interactive tool that enables users to benchmark vLLM endpoints through MCP, allowing performance testing of LLM models with customizable parameters.
A Model Context Protocol server that integrates with AWS CodePipeline, allowing users to manage pipelines through Windsurf and Cascade using natural language commands.
A utility that helps diagnose and fix GitHub Actions workflow failures by analyzing run logs, identifying common failure patterns, and suggesting specific fixes through a structured decision tree.
A Model Context Protocol service that wraps Django's migration commands as MCP endpoints, making it easy to manage migrations across multiple services and integrate with CI/CD pipelines.