"Popular and Secure Servers with High User Ratings" matching MCP servers:

Enables lifecycle-first governance for Edge AI fleets via MCP tools for approval requests, gate evaluation, and manual hold, ensuring deterministic deployment decisions with two-person approval, attestation, and safe rollback.

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.

Enables agents to run Playwright suites, diagnose failures from trace-level DOM, network and console evidence, and apply locator fixes that are re-run and reverted if still red. It also repeats failing tests for per-test flaky, regressed or broken verdicts and surfaces the same diagnosis and fix diffs in CI job summaries and PRs.

Enables interaction with Azure DevOps services through Personal Access Token authentication. Provides 75 tools for managing work items, builds, repositories, pull requests, and other DevOps operations via both CLI and HTTP API interfaces.

Enables natural language management of servers, deployments, and build pipelines through the Komodo infrastructure platform. It provides over 60 tools for automated workflows, real-time monitoring, and secure HMAC-authenticated infrastructure control.

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Enables AI agents and external systems to programmatically trigger and monitor Jenkins jobs, retrieve build status and logs via MCP standards.

Diffgate MCP server acts as a code review engine, enabling AI coding agents to analyze and validate code diffs before application. It enhances AI workflows by providing self-checking capabilities to optimise and secure code changes.

Fetches the latest version numbers for popular GitHub Actions from simonw/actions-latest, allowing users to easily check and update workflow versions.

Enables coding agents to access approved user stories and acceptance criteria via MCP, with tools to list, retrieve, update, and check story requirements against the working tree.

Enables AI coding agents and developers to perform secure, ultra-fast differential deployments over FTP, FTPS, and SFTP, inspect remote directory trees, test connectivity, and run dry-run diffs without exposing server credentials.

Enables autonomous AI agents and developers to interact with the GitHub REST API for repositories, pull requests, issues, actions, releases, tags, and user/org data through MCP tools. It uses token-efficient response summaries and optional 3-tier read-only safeguards to keep interactions safe and context-window friendly.

A secure MCP server providing read-only access to Argo CD instances using browser session cookies, enabling querying of applications, projects, clusters, and repositories.

An MCP server that connects LLMs to CERN GitLab to discover and analyze High Energy Physics code, documentation, and analysis examples. It provides 14 tools for repository browsing, dependency parsing, and CI/CD configuration analysis.

Lets MCP clients such as Claude or ChatGPT find the pull requests waiting on your review, read their details and changed files, check CI status, post comments, and submit approve, request-changes, or comment reviews. It runs locally over stdio with a personal token or as a remote server with its own OAuth 2.1 authorization server (PKCE, dynamic client registration, per-client consent, and refresh-token rotation) so GitHub is only used to sign the user in.

A GitHub-native secrets manager that allows AI assistants to securely manage, generate, and validate credentials without exposing sensitive values in conversation history. It supports secret scanning, environment diffing, and secure command execution by injecting masked variables directly into the runtime environment.

A specialized MCP server for QA engineering. It provides tools for user story analysis, test strategy, BDD/Gherkin scenarios, contract testing, integration tests, performance plans, security checklists, and CI/CD pipeline generation, accessible from any MCP-compatible IDE or client.

Enables AI assistants such as Claude, VS Code Copilot and Cursor to browse and modify Azure DevOps projects, work items, pull requests and pipelines through the Azure DevOps REST API, with a policy engine enforcing read-only defaults, dry-run diffs, one-time human approval tokens, project/branch scoping, secret redaction, rate limits and an audit log. Write and destructive operations stay gated behind explicit configuration and user confirmation, so agents can work with boards and pipelines without being handed full credentials.

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.

Provides secure access to containerized build environments for software projects, enabling AI assistants to execute builds, run tests, manage git operations, and inspect build artifacts without requiring local installation of dependencies.

A demonstration MCP server built with FastMCP v2.0 that provides basic mathematical calculations and greeting functionality. Features Docker containerization, comprehensive testing, and CI/CD automation for learning MCP development patterns.

A production-grade MCP server that gives AI agents secure, policy-controlled access to Coolify infrastructure, with least-privilege tokens, operation modes, allowlists, and secret redaction.

Enables Codex or Claude users to deploy applications and Compose services, inspect logs/databases/backups, patch environment variables, and manage Cloudflare DNS records and HTTPS domains through natural-language conversations, running locally with user-supplied credentials and preview/read-only safeguards.

Enables Claude to take a project from an empty folder to a published GitHub repository and npm, PyPI, or crates.io package. It automates preflight checks, scaffolding, quality checks, publishing, trusted-publishing setup, tagging, and release workflows, leaving only sign-in, 2FA, and approval clicks to the user.

Pre-install gate for AI coding agents. Checks npm, PyPI and crates.io package names before an install runs and blocks names that do not exist, were registered after models invented them, or sit one keystroke from a popular package. CLI, GitHub Action and MCP server. Apache 2.0.

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 TypeScript starter template for building Model Context Protocol (MCP) servers with built-in support for tools, testing, and CI/CD pipelines. It provides a complete development environment for creating custom AI assistant integrations for tools like Claude, Copilot, and Cursor.

Generates VS Code installation buttons and markdown badges for MCP servers, supporting both Stable and Insiders versions with configurable inputs and commands.

A lightweight MCP server providing a single tool to interact with Dagster instances via its GraphQL API for managing runs and logs. It features minimal token overhead and optional Cloudflare Access authentication for secure deployments.

A read-only MCP server that provides secure access to Bitbucket repositories, pull requests, issues, and more.