Alpic MCP Server for OpenAI Agents SDK 18 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Alpic through 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="Alpic Assistant",
instructions=(
"You help users interact with Alpic. "
"You have access to 18 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Alpic"
)
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 Alpic MCP Server
What you can do
Connect AI agents to the Alpic platform for complete MCP server lifecycle management:
The OpenAI Agents SDK auto-discovers all 18 tools from Alpic through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Alpic, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
- List and manage teams with member access controls
- Create, update, and delete MCP server projects with git repository linking
- Deploy to multiple environments (dev, staging, production) with one command
- Monitor deployments with real-time status, logs, and analytics
- Manage environment variables securely for each deployment target
- View analytics including request counts, latency, error rates, and usage patterns
- Publish to the MCP registry to make your servers discoverable
- Create development tunnels for local testing before production deployment
The Alpic MCP Server exposes 18 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 Alpic to OpenAI Agents SDK via MCP
Follow these steps to integrate the Alpic 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 18 tools from Alpic
Why Use OpenAI Agents SDK with the Alpic MCP Server
OpenAI Agents SDK provides unique advantages when paired with Alpic 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
Alpic + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Alpic MCP Server delivers measurable value.
Automated workflows: build agents that query Alpic, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Alpic, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Alpic tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Alpic to resolve tickets, look up records, and update statuses without human intervention
Alpic MCP Tools for OpenAI Agents SDK (18)
These 18 tools become available when you connect Alpic to OpenAI Agents SDK via MCP:
add_variable
Use this to set API keys, database URLs, feature flags, or any configuration needed by your MCP server. Requires project ID, environment ID, variable key, and value. Variable values are stored securely. Add a new environment variable to an Alpic environment
create_environment
Requires environment name and project ID. Optionally set initial variables and configuration. Each environment gets a unique URL for MCP client connections. Returns the created environment details. Create a new deployment environment (dev, staging, prod) for an Alpic project
create_project
Requires project name and team ID. Optionally set description, repository URL, and initial configuration. Returns the created project details including the new project ID needed for subsequent operations. Create a new MCP server project in Alpic
delete_project
This action cannot be undone. Use with caution. Requires the project ID. Confirm with the user before proceeding. Delete an Alpic MCP server project
delete_variable
Use this to clean up unused configuration keys. Requires project ID, environment ID, and variable key. Delete an environment variable from an Alpic environment
deploy_environment
The deployment runs asynchronously. Returns the deployment ID which can be used with get_deployment to check status. Use this to push new MCP server versions to dev, staging, or production environments. Trigger a new deployment for a specific Alpic environment
get_deployment
Requires the deployment ID. Use this to check if a deployment succeeded, review deployment history, or debug failed deployments. Get detailed status and metadata for a specific Alpic deployment
get_deployment_logs
Useful for debugging failed deployments, understanding build output, or verifying successful startup of the MCP server. Requires project ID and environment ID. Get deployment logs for a specific Alpic environment
get_project
Requires the project ID from list_projects results. Use this to review project settings before making updates or triggering deployments. Get detailed information about a specific Alpic MCP server project
get_project_analytics
Requires the project ID. Use this to monitor MCP server health, identify performance trends, and troubleshoot issues. Get analytics and usage data for a specific Alpic project
get_server_info
Use this to verify which MCP tools are exposed and confirm the server is running correctly. Get server information and status for a specific Alpic project
get_tunnel_ticket
Returns the tunnel URL and ticket token. Use this during development to test your MCP server before deploying to a production environment. Get a tunnel ticket for local development and testing of an MCP server
list_environments
Each environment has its own URL, variables, and deployment status. Returns environment IDs, names, URLs, and current deployment state. Use this to identify which environment to deploy to or manage variables for. List all environments (dev, staging, prod) for a specific Alpic project
list_projects
Returns project IDs, names, descriptions, associated teams, deployment status, and environment counts. Use this to overview your entire MCP infrastructure before managing specific projects or triggering deployments. List all MCP server projects in your Alpic account
list_teams
Each team contains projects and environments for deploying MCP servers. Returns team IDs, names, and member counts. Use this first to identify which team to manage projects under. List all teams associated with your Alpic account
list_variables
Variable values are masked for security. Returns variable keys and metadata. Use this to audit environment configuration before deploying or adding new variables. List all environment variables configured for an Alpic environment
publish_to_registry
Requires project ID and optionally a server description and category. Use this to make your MCP server publicly available. Publish an MCP server to the official MCP registry via Alpic
update_project
Only pass the fields you want to change. Requires the project ID from list_projects results. Use this to rename projects, update descriptions, or point to a new repository branch. Update an existing Alpic MCP server project configuration
Example Prompts for Alpic in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Alpic immediately.
"List all active Alpic projects running on my account natively, then check the error rate metric for the first one listed."
"Deploy the staging environment for our main enterprise project mapped on isolated branches."
"Audit the credentials in our production environment. Provide exact details of variable schemas missing from active lists."
Troubleshooting Alpic MCP Server with OpenAI Agents SDK
Common issues when connecting Alpic to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Alpic + OpenAI Agents SDK FAQ
Common questions about integrating Alpic 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 Alpic 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 Alpic to OpenAI Agents SDK
Get your token, paste the configuration, and start using 18 tools in under 2 minutes. No API key management needed.