Azure DevOps向けに構築された28個のMCPを発見。
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.
Manage and query Azure DevOps Boards and Work Items through a Model Context Protocol server.
Integrates with Azure DevOps to manage work items, wiki documentation, sprint planning, and handle attachments and discussions.
Aids in optimizing requirement engineering workflows by leveraging AI-driven insights and innovative coding methodologies.
Provides a Stdio-based interface for interacting with Azure DevOps resources as a .NET tool.
Provides a Model Context Protocol (MCP) server for Azure DevOps, enabling interaction with services via Personal Access Token (PAT) authentication.
Manages Azure DevOps work items through the Model Context Protocol (MCP) server.
Enables connecting to Azure DevOps data from Claude Desktop using CData JDBC Drivers.
Integrates Azure DevOps services into AI chat interfaces, enabling direct task management and information retrieval.
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.
Transforms standard input/output (stdio) MCP servers into accessible HTTP services, enabling centralized credential management and shared access for multiple clients.
Enables AI agents to interact with Azure DevOps projects, managing work items, wikis, and repositories.
Standardizes interactions between AI agents and backend systems through microservices.
Integrate Azure DevOps with AI assistants like VS Code/GitHub Copilot to manage work items directly from your chat interface.
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