Can I trigger a build for a specific branch through the agent?

Yes! Use the `trigger_cci_pipeline` tool. You need to provide the project slug (e.g., `gh/org/repo`) and the branch name. The agent will instruct CircleCI to start the pipeline immediately.

How do I see why a specific job failed?

Use the `get_job_details` tool with the project slug and job number. Your agent will fetch the execution status and metadata, which often points to the cause of failure.

Where do I find my CircleCI API Token?

Log in to CircleCI, go to **User Settings -> Personal API Tokens**. You can generate and copy a new token from there.

CircleCI MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: CircleCI
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to CircleCI through Vinkius, pass the Edge URL in the `mcps` parameter and every CircleCI 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

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="CircleCI Specialist",
    goal="Help users interact with CircleCI effectively",
    backstory=(
        "You are an expert at leveraging CircleCI 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 CircleCI "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

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

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 CircleCI MCP Server

Connect your CircleCI account to any AI agent and take full control of your CI/CD pipelines and software delivery through natural conversation. Streamline how you monitor and trigger automated builds.

When paired with CrewAI, CircleCI becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call CircleCI 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 Oversight — List and retrieve details for recent CI/CD pipelines across your organizations natively
Trigger Management — Manually trigger new pipeline runs for specific projects and branches flawlessly
Workflow Intelligence — Access detailed information for workflows and their constituent jobs securely
Job Auditing — Retrieve detailed metadata and execution status for specific jobs flawlessly
Context Logistics — List shared environment contexts used for securing sensitive project data flawlessly
Developer Insights — Retrieve your own user profile and organization membership information directly within your workspace

The CircleCI MCP Server exposes 8 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 CircleCI to CrewAI via MCP

Follow these steps to integrate the CircleCI 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 8 tools from CircleCI

Why Use CrewAI with the CircleCI MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with CircleCI 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

CircleCI + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries CircleCI 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 CircleCI, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain CircleCI 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 CircleCI against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

CircleCI MCP Tools for CrewAI (8)

These 8 tools become available when you connect CircleCI to CrewAI via MCP:

get_job_details

Get detailed information for a specific job

get_my_cci_profile

Retrieve information about the authenticated user

get_workflow_details

Get detailed information for a specific workflow

list_cci_contexts

List shared contexts for an organization

list_cci_pipelines

List recent CI/CD pipelines

list_pipeline_workflows

List all workflows within a specific pipeline

list_workflow_jobs

List all jobs within a specific workflow

trigger_cci_pipeline

Trigger a new pipeline for a project

Example Prompts for CircleCI in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with CircleCI immediately.

"List my last 5 pipelines in CircleCI."

"Trigger a new pipeline for project 'gh/acme/api' on the 'main' branch."

"Show me the status of all jobs in workflow ID 'wf-12345'."

Troubleshooting CircleCI MCP Server with CrewAI

Common issues when connecting CircleCI 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.

CircleCI + CrewAI FAQ

Common questions about integrating CircleCI 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.