Travis CI MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Travis CI through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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="Travis CI Assistant",
instructions=(
"You help users interact with Travis CI. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Travis CI"
)
print(result.final_output)
asyncio.run(main())
* 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 Travis CI MCP Server
Supercharge your DevOps methodology by linking Travis CI exclusively to your conversational agent. Stop tab-switching to discover broken build matrices. Instead, immediately drill down into repository health, trigger precise branches, or cancel looping jobs explicitly using semantic instructions from your active workspace.
The OpenAI Agents SDK auto-discovers all 10 tools from Travis CI through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Travis CI, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- Pipeline Discovery — List all repositories hooked natively into your Travis CI ecosystem and rapidly extract their internal ID or synchronization status
- Build Operations — Audit logs for specific branches, retrieve recent builds, or zoom in mathematically to inspect isolated "Jobs" operating within a single build
- Execution Command — Bypass graphic interfaces: Trigger fresh branch builds manually, force a strict "Restart" on a dead job, or rapidly "Cancel" a running test suite behaving poorly
- Branch Diagnostics — Call all tracked Git branches simultaneously to get an overview of their absolute latest build state
- Identity Sync — View your associated Dev profiles directly via the engine and list specific quotas or restrictions over your own session
The Travis CI MCP Server exposes 10 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.
How to Connect Travis CI to OpenAI Agents SDK via MCP
Follow these steps to integrate the Travis CI MCP Server with OpenAI Agents SDK.
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 10 tools from Travis CI
Why Use OpenAI Agents SDK with the Travis CI MCP Server
OpenAI Agents SDK provides unique advantages when paired with Travis CI 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
Travis CI + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Travis CI MCP Server delivers measurable value.
Automated workflows: build agents that query Travis CI, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Travis CI, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Travis CI tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Travis CI to resolve tickets, look up records, and update statuses without human intervention
Travis CI MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect Travis CI to OpenAI Agents SDK via MCP:
cancel_travis_build
This action is irreversible for the current execution. Cancels a currently running Travis CI build
get_build_details
Retrieves full details for a specific Travis CI build
get_repository_details
g. "org/repo") and need its ID or default branch status. Retrieves details for a specific Travis CI repository
get_user_profile
Retrieves the authenticated Travis CI user profile
list_build_jobs
Lists all individual jobs within a specific build
list_repository_branches
Lists all branches with their latest build status on Travis CI
list_repository_builds
Provide the repository slug. Lists recent build executions for a specific repository
list_travis_repositories
Lists all repositories configured on Travis CI
restart_travis_build
Requires the build ID. Restarts a previously executed Travis CI build
trigger_new_build
Provide the repo slug, git branch, and an optional message. Triggers a new Travis CI build for a repository on a specific branch
Example Prompts for Travis CI in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Travis CI immediately.
"Retrieve the build details for job execution ID #812323."
"Trigger a new deployment build on repo vinkius/core under main branch with message 'Hotfix'."
Troubleshooting Travis CI MCP Server with OpenAI Agents SDK
Common issues when connecting Travis CI to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Travis CI + OpenAI Agents SDK FAQ
Common questions about integrating Travis CI MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
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?
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?
Connect Travis CI with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Travis CI to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.