"Using Azure DevOps for Task Queries and Code Reviews" matching MCP servers:

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

Provides Azure DevOps tooling for AI agents, enabling interaction with projects, work items, repositories, and pipelines through natural language.

Enables AI agents to interact with Azure DevOps resources such as projects, builds, repositories, work items, test plans, and wikis through natural language using the Model Context Protocol.

A reference server implementation for the Model Context Protocol that enables AI assistants to interact with Azure DevOps resources and perform operations such as project management, work item tracking, repository operations, and code search programmatically.

Enables interaction with multiple Azure DevOps organizations simultaneously, providing access to pipelines, builds, repositories, and pull requests across different organizations without switching contexts or restarting the server.

About Search Steam games, fetch user reviews, and analyze sentiment with topic drill-down to make informed purchasing decisions.

Unified MCP server for DevOps engineers that provides real-time read and write access to Kubernetes, ArgoCD, Prometheus, and PagerDuty from any MCP-compatible AI agent.

An MCP server providing 69 tools for interacting with Azure DevOps, supporting both local deployment and remote Azure Functions deployment.

MCP server that scrapes Yandex Maps business reviews and company info, exposing them to AI assistants via three tools. No API key required, uses headless browser.

Enables interaction with Azure DevOps through Cursor chat, providing tools to manage builds, pipelines, work items, sprints, and board operations. Supports secure authentication via Personal Access Tokens and allows natural language-driven DevOps task management.

Enables natural-language queries about Azure resource compliance, including VM compliance, patch status, orphaned RBAC, and infrastructure health, through read-only MCP tools.

About Your task manager is the best agent memory you're not using. An agent-native context layer over your existing task app.

Provides persistent project memory, task lists, time tracking, and shared rules and learned preferences so coding agents can recall decisions and conventions across sessions and coordinate multi-step work.

Enables Azure SQL Database performance and administration through typed execution, query benchmarking, and managed DBA operations.

A secure MCP server providing controlled access to pixi tasks and commands, eliminating agent bash circumvention. It exposes 11 pixi tools through 4 meta-tools for ~95% context savings.

Enables AI agents to query and interact with Azure DevOps data, including work items, projects, ticket statistics, and backlog information through natural language commands.

Enables users to compare model-and-service-line offers against explicit task token ceilings and budgets, create expiring quotes, and record duplicate-safe simulated approvals through real MCP tools without executing models or making payments.

Connects AI assistants directly to Azure so users can manage infrastructure, resources, costs, security, and identities through plain-English conversation using their own Entra ID/RBAC permissions.

Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce — the server blocks the call if they don't. Works with any MCP-compatible client.

MCP server that wraps a personal task manager REST API, enabling Claude to read and manage tasks via tools like get_tasks and add_task.

Enables AI assistants to perform DevOps tasks including Kubernetes management, cloud provider operations, CI/CD, security scanning, and infrastructure monitoring through natural language.

Enables asynchronous task execution and scheduling using RabbitMQ, Celery, and Redis/SQLite. Supports immediate background task execution, scheduled tasks with ISO 8601 timestamps, task status monitoring, cancellation, and completion notifications.

Analyzes codebases from local directories, GitHub, and Azure DevOps, providing intelligent context to AI coding assistants through repository structure, critical files, and semantic maps.

This MCP server enables agents to manage complex tasks by providing tools for registration, complexity assessment, breakdown into subtasks, and status tracking throughout the task lifecycle.

Enables AI assistants to manage tasks through a comprehensive interface with 8 tools for creating, updating, searching, and tracking tasks with priorities, categories, and due dates. Features persistent file-based storage, advanced filtering, and task statistics for complete task management workflow.

Enables large language models to automatically report customer-facing issues with Azure resources by parsing natural language requests and submitting impact reports through the Azure Management API.

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.

Enables intelligent interaction with Azure resources through natural language by translating requests into safe, auditable Azure CLI commands with plan/review workflows and direct access to 8 Azure services including Storage, Cosmos DB, Key Vault, and more.

Turns AI assistants into full-stack software engineers with 36 tools for cognitive reasoning, code validation, project scaffolding, and AI/IDE configuration generation across 130+ programming languages, databases, and frameworks.

Open Task Relay provides free, bounded public-good tasks that autonomous AI agents can discover, complete, submit, and independently verify. Its public TypeScript source runs locally with a Cloudflare Workers-compatible runtime and SQLite/D1, exposing MCP over HTTP.