Where do I retrieve my API Token for Travis CI?

To obtain your credentials, log into your target `travis-ci.com` backend portal. Click your user avatar located prominently in the top right, expanding to access **Settings**. Look specifically under the API Authentication heading. Copy your displayed 'Token' verbatim. Deposit the string in the safe box below.

Can I permanently delete repositories via this interface?

No. The integration endpoints solely oversee execution boundaries (like manipulating jobs or active builds). Destructive endpoints concerning account integrity or unhooking internal repositories from version control simply do not exist in this scope.

Can I use a single API Token for both travis-ci.com and travis-ci.org?

No. Tokens for public projects (travis-ci.org), private projects (travis-ci.com), and Enterprise installations are not interchangeable. You must retrieve the token tightly bound to the specific environment you intend to integrate with.

Travis CI MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Travis CI
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Travis CI through Vinkius, pass the Edge URL in the `mcps` parameter and every Travis CI tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Travis CI Specialist",
    goal="Help users interact with Travis CI effectively",
    backstory=(
        "You are an expert at leveraging Travis CI tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Travis CI "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* 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.

When paired with CrewAI, Travis CI becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Travis CI tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Travis CI MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

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

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Travis CI

Why Use CrewAI with the Travis CI MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Travis CI through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Travis CI + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Travis CI MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Travis CI for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Travis CI, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Travis CI tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Travis CI against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Travis CI MCP Tools for CrewAI (10)

These 10 tools become available when you connect Travis CI to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

Common issues when connecting Travis CI to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Travis CI + CrewAI FAQ

Common questions about integrating Travis CI MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.