How to Use the Travis CI MCP in OpenAI Agents SDK

Q: Can I check if a specific branch is ready for deployment using OpenAI Agents SDK?

Absolutely. You can run listrepositorybranches to get all branches and their latest build status in one go. The agent reads that output, allowing it to decide if the main branch passed its tests.

Q: If a build fails, how do I restart it using OpenAI Agents SDK?

You'll use restarttravisbuild. You must pass the specific build ID that failed. This tool doesn't just retry; it actively restarts the previous execution for immediate debugging.

Q: Does the MCP Server support canceling a runaway CI process with OpenAI Agents SDK?

Yes. The canceltravisbuild tool lets your agent stop any currently running build immediately. This action is irreversible, so use it only when you know the job needs to be terminated.

Manage CI/CD pipelines and enforce build integrity with your OpenAI Agents SDK agent.

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Connect Travis CI MCP to OpenAI Agents SDK

Create your Vinkius account to connect Travis CI to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Travis CI with OpenAI Agents SDK

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Triggering new deployments

Need to kick off a fresh test run? Use `trigger_new_build` to start a Travis CI job. You just provide the repo slug, the branch name, and an optional message for context. It’s perfect for automated workflows. If you change the code base, your agent can call this tool immediately after checking out the latest commit.

Inspecting build history

Don't want to sift through logs? Call `list_repository_builds` when you just need a rundown of recent executions for a specific repository. You can also get detailed lists using `list_build_jobs` once you have the main build ID. This gives your agent a clear picture, letting it quickly identify if a failure happened three days ago or five minutes ago.

Retrieving core repository data

Start with `list_travis_repositories` to see every project configured on Travis CI. Once you have the right slug, use `get_repository_details` for specific information and status checks. You can also check out who ran the build using `get_user_profile`, ensuring the actions taken are logged against the correct account.

Setup guide

Set up Travis CI MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Travis CI tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Travis CI tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Travis CI tools and returns structured results. Copy the full example on the right to get started.

agent.py

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

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Travis CI Agent",
            instructions="You have access to Travis CI tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Travis CI MCP in OpenAI Agents SDK

Your agent uses the MCP Server to manage the lifecycle. It first calls `list_travis_repositories` to confirm the target project, then runs `trigger_new_build`. This whole sequence keeps your deployments automated and secure.

Absolutely. You can run `list_repository_branches` to get all branches and their latest build status in one go. The agent reads that output, allowing it to decide if the main branch passed its tests.

You'll use `restart_travis_build`. You must pass the specific build ID that failed. This tool doesn't just retry; it actively restarts the previous execution for immediate debugging.

The server touches 'build status information.' Your AI client handles authentication, and all actions are logged against your authenticated user profile. You maintain full control over who can trigger or cancel builds.

Yes. The `cancel_travis_build` tool lets your agent stop any currently running build immediately. This action is irreversible, so use it only when you know the job needs to be terminated.

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