Can I see if a build pipeline failed via the AI?

Yes! Use the `list_builds` tool and provide the Project ID. Your agent will retrieve the history of recent executions, including their final status (succeeded, failed, inProgress).

How do I list the Git repositories for a project?

Run the `list_repositories` query with your Project ID. The agent will return all Git repositories associated with that project in your Azure DevOps account.

Is it possible to see recent bugs or tasks assigned to a project?

Absolutely. Use the `list_work_items` tool. Your agent will retrieve a list of recent work items, including bugs, tasks, and stories, for the specified project.

INSTANT PLUG AND PLAY

Azure DevOps MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 6 tools to List Builds, List Pipelines, List Project Teams, and more

Name: Azure DevOps
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 6 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Azure DevOps through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Use with Your AI Agent

Ask AI about this App Connector for OpenAI Agents SDK

Open in ChatGPT Open in Claude Open in Perplexity

The Azure DevOps app connector for OpenAI Agents SDK is a standout in the Industry Titans category — giving your AI agent 6 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Azure DevOps Assistant",
            instructions=(
                "You help users interact with Azure DevOps. "
                "You have access to 6 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Azure DevOps"
        )
        print(result.final_output)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Azure DevOps MCP Server

Connect your Azure DevOps account to any AI agent and simplify how you manage your software development lifecycle, track work items, and monitor pipelines through natural conversation.

The OpenAI Agents SDK auto-discovers all 6 tools from Azure DevOps through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Azure DevOps, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Project Oversight — List all projects in your organization and retrieve detailed metadata and configurations.
Work Item Tracking — List and query recent tasks, bugs, and user stories to manage your team's backlog.
Git Repository Control — Query all Git repositories within a project to monitor code storage.
Pipeline Monitoring — List CI/CD pipelines and retrieve the history of recent build executions and statuses.
Team Coordination — List project teams to understand organizational structure and distribution.
Operational Status — Fetch real-time metadata for projects and work items directly via AI commands.

The Azure DevOps MCP Server exposes 6 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 6 Azure DevOps tools available for OpenAI Agents SDK

When OpenAI Agents SDK connects to Azure DevOps through Vinkius, your AI agent gets direct access to every tool listed below — spanning ci-cd, pipeline-management, work-item-tracking, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

list_builds

List recent builds

list_pipelines

List CI/CD pipelines

list_project_teams

List teams in a project

list_projects

List Azure DevOps projects

list_repositories

List Git repositories

list_work_items

List recent work items

Connect Azure DevOps to OpenAI Agents SDK via MCP

Follow these steps to wire Azure DevOps into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 6 tools from Azure DevOps

Why Use OpenAI Agents SDK with the Azure DevOps MCP Server

OpenAI Agents SDK provides unique advantages when paired with Azure DevOps through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Azure DevOps + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Azure DevOps MCP Server delivers measurable value.

Automated workflows: build agents that query Azure DevOps, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Azure DevOps, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Azure DevOps tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Azure DevOps to resolve tickets, look up records, and update statuses without human intervention

Example Prompts for Azure DevOps in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Azure DevOps immediately.

"List all active projects in my Azure DevOps organization."

"Show me the last 5 work items for the 'Mobile App' project."

"What is the status of the latest build for project 'Internal Tools'?"

Troubleshooting Azure DevOps MCP Server with OpenAI Agents SDK

Common issues when connecting Azure DevOps to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Azure DevOps + OpenAI Agents SDK FAQ

Common questions about integrating Azure DevOps MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.

Can I use multiple MCP servers in one agent?

Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.

Does the SDK support streaming responses?

Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with Vinkius.