"Qdrant vector database and search engine" 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.

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

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.

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.

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.

An MCP server that scaffolds full-stack projects with consistent structure, Docker setup, CI/CD pipelines, and database configuration.

Developers are constantly feeding context files to AI tools like Cursor, Windsurf, Copilot Workspace, and Claude Code. If your agent doesn't understand your real database schema, it writes code that fails in production. LintBase acts as the bridge. It connects directly to your database, reads the ground truth of your live documents, and generates structured context optimized for AI. 🤖 Stops AI

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

Blocks unsafe PostgreSQL migrations before an AI agent writes or runs them. check_before_apply returns a pass/fail gate; reads the real Postgres parser, classifies the lock each statement takes, checks 112 safety rules. Runs offline, no database required.

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.

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.

MCP server that runs Flyway repair + migrate across multiple database projects for QA or Development environments.

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.

An MCP server that enables AI assistants to manage database migrations and validate schemas using the Ariga Atlas CLI. It provides tools for applying migrations, generating diffs, linting, and checking migration status through natural language.

Enables interaction with GitHub repositories, issues, pull requests, code search, branches, and GitHub Actions workflows.

Integrates Ploi.io API functionality into AI assistants for managing servers, sites, and databases through natural language. It enables features like one-command deployments, project linking, server log retrieval, and database backup management.

MCP server for Sqemo, a web-based ERD tool with team naming standards. 34 tools: read/edit entities, attributes, and relationships; generate physical names from a shared glossary and naming rules; SQL (7 dialects) and DBML import/export; ERD lint, diff, and ALTER generation.

Enables AI assistants to interact with Netflix Conductor Workflow Engine for troubleshooting workflows, managing executions, and creating/updating workflow and task definitions through natural language.