Cloudify MCP Server for AutoGen 7 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Cloudify as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="cloudify_agent",
tools=tools,
system_message=(
"You help users with Cloudify. "
"7 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
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 Cloudify MCP Server
Connect your Cloudify Manager to any AI agent and take full control of your multi-cloud orchestration through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Cloudify tools. Connect 7 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Blueprint Management — List and audit OASIS TOSCA blueprints parsing root Cloudify manager templates
- Deployment Tracking — Retrieve exact structural matching of actualized runtime schemas and manage infrastructure states
- Workflow Executions — Monitor install, uninstall, and heal transactions to track deployment events in real-time
- Node Inspections — Resolve deeply nested infrastructure nodes and audit lifecycle properties (started, created, deleted)
- Plugin Auditing — Discover installed Python abstractions for AWS, GCP, and other cloud integrations
The Cloudify MCP Server exposes 7 tools through the Vinkius. Connect it to AutoGen 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 Cloudify to AutoGen via MCP
Follow these steps to integrate the Cloudify MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 7 tools from Cloudify automatically
Why Use AutoGen with the Cloudify MCP Server
AutoGen provides unique advantages when paired with Cloudify through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Cloudify tools to solve complex tasks
Role-based architecture lets you assign Cloudify tool access to specific agents. a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Cloudify tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Cloudify tool responses in an isolated environment
Cloudify + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Cloudify MCP Server delivers measurable value.
Collaborative analysis: one agent queries Cloudify while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Cloudify, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Cloudify data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Cloudify responses in a sandboxed execution environment
Cloudify MCP Tools for AutoGen (7)
These 7 tools become available when you connect Cloudify to AutoGen via MCP:
get_blueprint
Perform structural extraction of properties driving active blueprint schemas
get_deployment
Extracts explicitly attached internal structural states pulling precise execution topologies
list_blueprints
Identify bounded logical arrays managing top-level orchestration schemas
list_deployments
Retrieve the exact structural matching verifying actualized runtime schemas
list_executions
Identify precise active cluster limits spanning deployment workflow bounds
list_nodes
Identify exact literal limits pushing specific instances routing orchestration rules
list_plugins
Extracts explicit capabilities mapping native orchestration limits
Example Prompts for Cloudify in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Cloudify immediately.
"List all blueprints in Cloudify Manager"
"Show me the execution history for deployment 'web-app-prod'"
"What nodes are currently in the 'started' state for deployment 'db-cluster'?"
Troubleshooting Cloudify MCP Server with AutoGen
Common issues when connecting Cloudify to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Cloudify + AutoGen FAQ
Common questions about integrating Cloudify MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
Connect Cloudify 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 Cloudify to AutoGen
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.