"How to send queries to an Elasticsearch cluster" matching MCP servers:

An MCP server that adds engineering discipline to AI-assisted development, enforcing evidence-gated TDD, security review, backup strategy, and deployment generation to turn AI-generated code into production-ready software.

Converts Jenkins declarative pipelines into GitHub Actions workflow YAML files, facilitating migration from Jenkins to GitHub Actions CI/CD.

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.

Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.

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.

Provides disposable email inboxes for AI agents to automatically receive and extract OTPs and magic links, enabling seamless email verification during autonomous workflows.

An MCP server that provides deterministic tools for AI assistants to standardize development workflows, including branch naming, commit validation, and PR checklists.

MCP server that triggers Jenkins automation jobs and returns their results, with an action registry, parameter validation, and credential redaction.

An MCP server that enables AI assistants to interact with Apache Airflow's REST API for DAG management, task monitoring, and system diagnostics. It provides comprehensive tools for triggering workflows, retrieving logs, and inspecting system health across Airflow 2.x and 3.x versions.

An MCP server that drives Google Play releases: bundle upload, track releases (internal/closed/open/production), listing metadata, store graphics, and review replies.

An MCP server that drives the full App Store release cycle for iOS and macOS apps: version bump, archive + TestFlight upload, metadata, review submission, and status.

MCP server that automates the publishing and validation of Tableau workbooks and data sources on Tableau Server or Tableau Cloud, enabling an AI agent to discover, build, validate, and publish content without human intervention.

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.

An MCP server that lets AI agents discover Ansible Galaxy collection input/output contracts, including module arguments, return values, and role facts, to help generate accurate playbooks.

Exposes tools to list, run, and inspect GitHub Actions workflows locally via act, enabling debugging and fixing failures through an agent loop.

An MCP server that gives AI agents full access to the Harness.io platform through 11 consolidated tools and 207 resource types.

Enables MCP-speaking agents to deploy and operate applications on gagarin by translating every tool call into an authenticated request to the gagarin API, using the caller's own credential.

Enables natural language interactions with CircleCI through Model Context Protocol, allowing users to retrieve build logs, find flaky tests, check pipeline statuses, and manage workflows without leaving their IDE.

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.

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