"How to interact with an Azure DevOps repository" 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.

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

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.

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

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

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.

Enables agents to break high-level business objectives into dependency-ordered sub-task graphs and then directly generate the finished deliverables, such as financial spreadsheets, executive presentations, and analytical reports. It runs as a zero-dependency Python MCP server over JSON-RPC stdio, adding deterministic authorization, role-boundary validation, and telemetry.

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 AI agents to interact with ActiveNet OpenAPI services for managing organizations, activities, customers, facilities, and more.

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.