Pulumi MCP Server for OpenAI Agents SDK 11 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Pulumi through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Pulumi Assistant",
instructions=(
"You help users interact with Pulumi. "
"You have access to 11 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Pulumi"
)
print(result.final_output)
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 Pulumi MCP Server
Connect your Pulumi account to any AI agent and take full control of your infrastructure-as-code through natural conversation.
The OpenAI Agents SDK auto-discovers all 11 tools from Pulumi through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Pulumi, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- Organization Discovery — List organizations and retrieve their details, team settings and member info
- Stack Management — List, create and delete stacks (infrastructure environments) across all your projects
- Deployment Tracking — Monitor stack update history with status (succeeded, failed, in-progress), resource changes and error logs
- Output Inspection — View exported output values from the latest deployment (URLs, IPs, resource IDs)
- Tag Management — List and set custom tags on stacks for organization and filtering (environment, team, cost-center)
The Pulumi MCP Server exposes 11 tools through the Vinkius. Connect it to OpenAI Agents SDK 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 Pulumi to OpenAI Agents SDK via MCP
Follow these steps to integrate the Pulumi MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 11 tools from Pulumi
Why Use OpenAI Agents SDK with the Pulumi MCP Server
OpenAI Agents SDK provides unique advantages when paired with Pulumi through the Model Context Protocol.
Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Pulumi + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Pulumi MCP Server delivers measurable value.
Automated workflows: build agents that query Pulumi, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries Pulumi, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Pulumi tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Pulumi to resolve tickets, look up records, and update statuses without human intervention
Pulumi MCP Tools for OpenAI Agents SDK (11)
These 11 tools become available when you connect Pulumi to OpenAI Agents SDK via MCP:
create_stack
A stack is an isolated, independently configurable instance of your Pulumi program. Requires the org name, project name and stack name (e.g. "staging", "prod"). Returns the created stack with its URL. Create a new Pulumi stack
delete_stack
The stack must be empty (no resources) or force deletion must be enabled. Provide the org name, project name and stack name. WARNING: this action is irreversible. Delete a Pulumi stack
get_current_user
Returns the user's GitHub login, avatar URL, email and name. Use this to verify your access token is working correctly and to see which identity the API calls will appear as. Get the currently authenticated Pulumi user
get_deployment
Provide the org name, project name, stack name and deployment version number. Get details for a specific Pulumi deployment
get_organization
Provide the organization name (slug). Get details for a specific Pulumi organization
get_stack
Provide the org name, project name and stack name. Get details for a specific Pulumi stack
get_stack_outputs
Outputs are values your Pulumi program exports, such as URLs, IP addresses, resource IDs and connection strings. Useful for discovering endpoint addresses and configuration values after infrastructure deployment. Get the exported output values from a Pulumi stack
list_deployments
Each deployment shows its version number, status (succeeded, failed, in-progress), start/end time, resource changes (created, updated, deleted) and the user who triggered it. Use this to audit infrastructure changes and track deployment success/failure patterns. List deployment history for a Pulumi stack
list_stack_tags
Tags are key-value metadata labels used for organizing, filtering and managing stacks (e.g. environment=prod, team=platform, cost-center=engineering). List tags on a Pulumi stack
list_stacks
Each stack represents an isolated, independently configurable instance of your infrastructure (e.g. dev, staging, prod). Returns stack name, project name, last update info, resource count and whether updates are in progress. List all stacks in a Pulumi organization
set_stack_tag
Tags are used for organizing, filtering and managing stacks (e.g. key="environment", value="prod", key="team", value="platform"). Provide the org name, project name, stack name, tag name and tag value. Set a tag on a Pulumi stack
Example Prompts for Pulumi in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Pulumi immediately.
"Show me all stacks in my organization."
"What was the result of the latest deployment to my-infra/prod?"
"Show me the exported outputs from the prod stack."
Troubleshooting Pulumi MCP Server with OpenAI Agents SDK
Common issues when connecting Pulumi to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Pulumi + OpenAI Agents SDK FAQ
Common questions about integrating Pulumi MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Pulumi 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 Pulumi to OpenAI Agents SDK
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.