"A search engine focused on privacy and minimal tracking" matching MCP servers:

MCP server for IBM Code Engine — build, push, and deploy containers from Cursor, Copilot, Claude, and Cline using natural language.

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.

MCP server for Azure DevOps Server 2022 (on-premises) that enables AI assistants to interact with work items, repositories, builds, and sprints through 29 tools.

MCP server wrapping the full VitoDeploy REST API to manage projects, servers, sites, databases, services, workers, SSL, DNS, and more through any MCP-compatible agent, with 108 tools covering every endpoint.

A LangGraph-powered MCP server for infrastructure orchestration with autonomous subagents.

AI code review against your team's own rules from your repository, before the pull request: two tools, review_changes and get_team_rules. Closed-source binary distributed via GitHub Releases; published in the official MCP Registry as dev.reviewgate/reviewgate.

A security-focused MCP server for self-hosted n8n Community Edition, providing 44 bounded tools to manage workflows, nodes, executions, credentials, tags, and more via the n8n Public API.

A lightweight, powerful, and flexible workflow engine that executes tasks defined in YAML configuration files.

Local CI/CD engine for AI agents. ActionD listens to LGH git events and runs plugin jobs (Go/Python/Java/web toolchains) in isolated checkouts, with structured results, root-cause failure diagnosis, approval gates, and auto-rollback. The MCP server exposes 23 tools, including dev_cycle_run (commit → CI → structured verdict in one call) and actiond_diagnose for failed-job analysis.

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.

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.

Enables AI coding agents to orchestrate the full software development lifecycle on GitHub, including planning, issue creation, code review, security triage, and release readiness checks.

Deploys and manages projects on Swigs Cloud from any MCP client, turning folders or git repositories into live HTTPS sites in about two minutes.

Enables AI agents to deploy, manage, and configure web applications on sota.io, including project creation, deployment, environment variables, custom domains, and rollbacks.

MCP server that audits npm dependencies against the live registry, providing per-dependency reports on versions behind, deprecation, and license.

Enables AI agents to query summit registration and forum analytics, review code changes for risks, run fixed quality gates, and perform audited, permission-controlled commits and deployments with minimal access and human approval.

Production-ready, zero-knowledge AI DevOps deployment, infrastructure provisioning, self-healing execution, and persistent documentation engine for VPS servers.

MCP security trust layer. Continuously monitors 800+ MCP packages on npm for install scripts, command injection, hardcoded secrets, capability drift, and publisher posture. Ships a GitHub Action policy gate for PR-level allow/warn/block decisions. 5 MCP tools, no API key required.

Publishes static sites to Drop2Run from an AI agent: hand it files written in the chat or a folder on disk, and it returns a live HTTPS URL. Six tools — publish_files, publish_dir, list_sites, delete_site, and login / login_code — with no git, no build step and no repository.

A comprehensive and efficient Model Context Protocol server for task management that works with Claude, Cursor, and other MCP clients, providing powerful search, filtering, and organization capabilities across multiple file formats.