"Natural Language to SQL Conversion and Executing MySQL Queries to Retrieve Data" 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.

Enables running SQL warehouse validation checks through natural-language questions in MCP clients, while reusing the same logic for automated pipeline and CI/CD runs.

Enables developers to manage Genesys Cloud Function Data Actions through natural language in Cursor, including validating, building, planning, and applying function deployments while enforcing safety controls like plan-before-apply and read-only mode.

MCP aggregator with many existing NCP templates and allows running external MCP servers too

Zero-config data quality monitoring as MCP tools. Profiles a warehouse (Postgres, BigQuery, Snowflake, MySQL, DuckDB), detects anomalies, and gates CI — read-only with the connection resolved server-side, never via the model.

Enables interaction with Rundeck instances to list jobs, execute jobs with options, and retrieve execution status and logs through natural language commands.

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.

Enables AI assistants to manage CData Sync operations, including data synchronization jobs, connections, and ETL processes through stdio or HTTP transports. It provides tools for executing jobs, monitoring real-time progress via Server-Sent Events, and handling comprehensive workspace configurations.

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

Enables monitoring and debugging of Hatchet workflows and jobs through MCP clients like Claude Code. Users can list workflows, track run statuses, query queue metrics, and retrieve job results using natural language commands.

A local MCP server that exposes Blacksmith.sh's usage and cost data, enabling queries for CI spend through agents, alerts, or dashboards.

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.

Connects AI assistants to GitLab to interact with merge requests, reviews, discussions, pipelines, and test results through natural language queries. Supports viewing MR details, responding to comments, checking test summaries, and analyzing job logs.

Provides tools to interact with Fedora Copr, enabling users to manage projects, builds, and packages through natural language.

Enables AI assistants to manage Bitbucket Cloud repositories, pull requests, pipelines, and code review tasks through natural language.

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 manage Rundeck operations including jobs, executions, projects, nodes, system management, key storage, webhooks, and ACL policies via natural language.

Enables AI assistants to interact with Atlassian Bamboo CI/CD, allowing natural language queries to check build status, fetch logs, trigger builds, and manage deployments.

Enables AI assistants to interact with SemaphoreUI for managing and running Ansible automation tasks through natural language commands.