"Slack Bot with RAG Document Retrieval and Automated Response System" matching MCP servers:

Enables triggering Jenkins builds from IDEs with Slack notifications, requiring only a one-time login.

Enables interaction with Slack channels including checking Xcode Cloud build status, reading and searching messages, sending messages, and listing channels.

Enables sending customizable Slack notifications from Claude, supporting rich formatting, task completion alerts, and priority levels for development workflows.

A production-grade MCP server with 6 sandboxed tools and an agent orchestration engine for autonomous task completion, featuring an evaluation suite with CI/CD quality gates.

Automates routine DevOps tasks like Jenkins builds and GitLab merge requests through the MCP protocol, simplifying daily operations.

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.

This MCP server enables intelligent API testing automation by combining RAG knowledge retrieval with tool execution capabilities. It allows QA engineers to perform natural language-driven API testing with contextual knowledge support.

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.

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

Demonstrates how to deploy and run Model Context Protocol (MCP) servers using Netlify's serverless functions. Provides a basic example of serverless MCP implementation with customizable URLs and automated deployment pipeline.

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

Enables AI clients to assess infrastructure-as-code deployment risk, generate incident response runbooks, review CI/CD delivery readiness, and calculate SLO error budgets through structured advisory tools. Runs locally over stdio without cloud credentials or external API calls, returning guidance for platform work, pull request review, and production readiness checks.

Enables AI coding tools to validate local projects and publish or update applications to Bedengan App Hub via API, with automated checks and live deployment without manual approval.

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.

Baron gives an AI coding agent one normalized contract for work orchestration: create and transition issues, cut branches, open and merge pull requests, and read CI and deployment status across Azure DevOps, GitHub and Slack.

Enables AI assistants to answer questions about nixpkgs packages using nixkeeper's public data, covering outdated versions, Hydra build status and failures, update-bot attempts, related PRs and issues, CVEs, and what needs attention for a maintainer or team. It runs locally over stdio, reads only public data, and requires no account or token.

MCP server and CLI for AlmaLinux Build System (ALBS) that enables AI coding assistants to investigate build failures, create builds, sign packages, and manage release plans through natural language.

Enables automated packaging of Maven backend and npm frontend projects, with SVN version retrieval and both step-by-step and one-click build workflows.

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.

An MCP server that automates the full software development lifecycle through an AI-driven TDD state machine. It handles everything from task decomposition and test-driven development to integration testing and automated pull request creation.