Discover 22 MCPs built for Azure DevOps.
Integrates Azure DevOps capabilities directly into development environments by providing a local server that enables interaction with various services.
Provides Python APIs for interacting with and managing Azure DevOps services.
Facilitates interaction with Azure DevOps services through AI assistants by providing entity-based tools.
Enables AI agents to automate and manage Azure DevOps operations, including boards, repositories, pipelines, artifacts, test plans, and wikis.
Integrates Azure DevOps with Cursor IDE, providing access to projects, work items, repositories, and pull requests.
Enables management of Azure DevOps projects and repository operations through an API.
Aids in optimizing requirement engineering workflows by leveraging AI-driven insights and innovative coding methodologies.
Integrates with Azure DevOps to manage work items, wiki documentation, sprint planning, and handle attachments and discussions.
Enables connecting to Azure DevOps data from Claude Desktop using CData JDBC Drivers.
Manages Azure DevOps authentication and context dynamically, allowing seamless integration with multiple projects and organizations from a single server instance.
Integrates with Azure DevOps to manage backlogs, work items, and execute queries via a standardized Model Context Protocol (MCP) interface.
Empowers AI assistants to manage and retrieve information from Azure DevOps services using natural language.
Integrates Azure DevOps services into AI chat interfaces, enabling direct task management and information retrieval.
Provides a Model Context Protocol (MCP) server for Azure DevOps, enabling interaction with services via Personal Access Token (PAT) authentication.
Enables AI agents to interact with Azure DevOps projects, managing work items, wikis, and repositories.
Manages Azure DevOps work items through the Model Context Protocol (MCP) server.
Integrates Azure DevOps with GitHub Copilot Chat, enabling natural language queries for work items directly within your IDE.
Standardizes interactions between AI agents and backend systems through microservices.
Integrate Azure DevOps services and context directly into development agents and code editors.
Facilitates interaction with the Azure DevOps API, enabling project management and repository operations.
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