"How to integrate with Azure DevOps" matching MCP servers:

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

The Azure MCP Server, bringing the power of Azure to your agents.

Enables AI assistants to interact with Alibaba Cloud Yunxiao DevOps platform for managing projects, code repositories, work items, pipelines, deployments, and testing workflows through comprehensive organization, development, and delivery tools.

Enables face detection and recognition in Agentic AI workflows using Azure Face API, supporting attribute detection, image comparison, and face recognition.

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

This read-only MCP Server allows you to connect to Azure Analysis Services data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

A remote MCP server (Node.js/TypeScript) deployed on Azure Container Apps that provides todo list management tools with JWT authentication and role-based access control.

An AI-powered containerization assistant that helps you build, scan, and deploy Docker containers through VS Code and other MCP-compatible tools.

This read-only MCP Server allows you to connect to Azure Data Lake Storage data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Enables comprehensive DevOps infrastructure management through tools for Jenkins, Ansible, Terraform, Kubernetes, and Docker operations. Features a sophisticated memory system for context retention and provides validation, generation, and optimization capabilities across DevOps workflows.

Thin MCP server that enables AI agents to generate video, image, and audio content via the Deepy API using a personal API key, with safe generation flow and no business logic.

Enables querying of a locally pinned snapshot of the Education-to-Workforce Indicator Framework — 99 indicators and 11.8M observations — to browse questions, describe metrics, resolve places, and fetch or rank data across national, state, county, and district levels.

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.

MCP server that enables Claude and GitHub Copilot to interact with the Tracelink API for managing company data, orders, objects, and journal entries.

Provides LLM access to Exasol database via MCP tools, including metadata reading and data queries, with an optional on-premise text-to-SQL (Governed SQL) translation.

Enables agents to discover available still-image animation models, obtain credit quotes without charge, submit one explicitly approved generation job, and poll the resulting short clip.

Enables AI agents to browse pizza menus, place orders, and track order status via the Model Context Protocol.

Lightweight project management for teams and AI agents.

MCP server for Precogly threat modeling, enabling users to integrate threat modeling capabilities into AI assistants.