How to Use the Daytona (Dev Workspaces) MCP in CrewAI
Deploy specialized CrewAI agent teams to provision, test, and manage Daytona dev environments autonomously.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Daytona (Dev Workspaces) MCP to CrewAI
Create your Vinkius account to connect Daytona (Dev Workspaces) to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Multi-Agent Environment Provisioning
Let a QA agent and a DevOps agent collaborate to prepare test environments. The DevOps agent calls `create_sandbox` to spin up the workspace, while the QA agent monitors the build status. Once the environment is ready, the QA agent uses `get_sandbox_preview_url` to run integration tests against the live port. If tests fail, the agents work together to diagnose the issue without human intervention.
Autonomous Sandbox Lifecycle Management via MCP Server
Deploy a moderator agent to keep your cloud spend down. This agent periodically calls `list_sandboxes` to check for inactive workspaces and automatically shuts them down using `stop_sandbox`. If a developer needs their workspace back, they ask the assistant, which triggers `start_sandbox` to wake it up. This MCP Server setup ensures you never leave expensive sandboxes running overnight.
Automated Snapshot and Archive Crews
Set up a dedicated backup crew that monitors your active development environments. The crew uses `create_snapshot` to capture daily progress and archives old work using `archive_sandbox`. If an environment gets corrupted, the recovery agent steps in, runs `recover_sandbox`, and restores the latest snapshot. It keeps your development team moving without manual infrastructure troubleshooting.
Set up Daytona (Dev Workspaces) MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically. - 3
Kick off your crew
Create a
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke Daytona (Dev Workspaces) tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Daytona (Dev Workspaces) Analyst",
goal="Access and analyze Daytona (Dev Workspaces) data via MCP.",
backstory="Expert analyst with direct Daytona (Dev Workspaces) access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Daytona (Dev Workspaces) transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters
server_params = SseServerParameters(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
with MCPServerAdapter(server_params) as mcp_tools:
agent = Agent(
role="Daytona (Dev Workspaces) Analyst",
goal="Access and analyze Daytona (Dev Workspaces) data via MCP.",
backstory="Expert analyst with direct Daytona (Dev Workspaces) access.",
tools=mcp_tools,
)
task = Task(
description="List recent Daytona (Dev Workspaces) transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Daytona. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Real-time monitoring
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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
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60%
lower AI costs
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Common questions about Daytona (Dev Workspaces) MCP in CrewAI
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