How do I obtain a MasterGo API Token?

Log in to MasterGo, go to the [Developer Center](https://mastergo.com/developers), and create a new application or generate a personal access token under your account settings.

Can I read specific layer information through this server?

Yes. Use the `list_nodes` tool with the file key and optional node IDs. This allows your agent to retrieve detailed data about frames, layers, and their properties.

What is a 'fileKey' in MasterGo?

The `fileKey` is the unique identifier found in the URL of your MasterGo design file. It typically appears after `/file/` in the browser address bar.

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

Name: MasterGo
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to MasterGo through Vinkius, pass the Edge URL in the `mcps` parameter and every MasterGo 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="MasterGo Specialist",
    goal="Help users interact with MasterGo effectively",
    backstory=(
        "You are an expert at leveraging MasterGo 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 MasterGo "
        "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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IAMAccess control

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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 MasterGo MCP Server

Empower your AI agent to orchestrate your design workflow with MasterGo, the leading professional design tool for high-performance team collaboration. By connecting MasterGo to your agent, you transform complex design file navigation and project coordination into a natural conversation. Your agent can instantly list your files, retrieve design nodes (frames and layers), audit style libraries, and even browse version history without you ever needing to navigate the complex design workspace. Whether you are managing a large-scale design system or a specific UI project, your agent acts as a real-time design assistant, keeping your assets organized and your team aligned.

When paired with CrewAI, MasterGo becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call MasterGo 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

File Orchestration — List all accessible design files and projects across your MasterGo workspace.
Node Management — Retrieve granular design nodes and layers to understand your UI structure instantly.
Collaboration Monitoring — Browse file comments and organization members to stay informed about team updates.
Style Auditing — List defined design styles, including colors and typography, across your files.
Version Control — Check the version history of design files to track changes and milestones.

The MasterGo 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 MasterGo to CrewAI via MCP

Follow these steps to integrate the MasterGo 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 MasterGo

Why Use CrewAI with the MasterGo MCP Server

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

MasterGo + CrewAI Use Cases

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

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

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

MasterGo MCP Tools for CrewAI (10)

These 10 tools become available when you connect MasterGo to CrewAI via MCP:

get_comments

Get file comments

get_file

Get design file details

get_file_versions

Get file version history

get_org_members

List organization members

get_project_files

Get project files

list_files

List all MasterGo files

list_nodes

List nodes in a file

list_projects

List team projects

list_styles

List file styles

list_teams

List available teams

Example Prompts for MasterGo in CrewAI

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

"List all design files in my MasterGo workspace."

"Show me the comments for file 'design-8821'."

"Retrieve the style library for file 'core-ui-library'."

Troubleshooting MasterGo MCP Server with CrewAI

Common issues when connecting MasterGo 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.

MasterGo + CrewAI FAQ

Common questions about integrating MasterGo 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.