SwaggerHub MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect SwaggerHub 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="SwaggerHub Assistant",
instructions=(
"You help users interact with SwaggerHub. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from SwaggerHub"
)
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 SwaggerHub MCP Server
Integrate SwaggerHub, the enterprise platform for API design and documentation, directly into your conversational workflows with the intelligent MCP connector. Transform your LLM into an active technical architect, empowering it to securely index, validate, and retrieve full OpenAPI specifications directly from your organizational directories. Eradicate context-switching by verifying CI/CD integration pipelines, scanning centralized API definitions, and pulling structural component domains intuitively without having to hunt through graphical interfaces.
The OpenAI Agents SDK auto-discovers all 10 tools from SwaggerHub through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries SwaggerHub, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- API Cataloging & Specs — Query an entire organizational API roster using
list_apisand pull exact OpenAPI JSON configurations cleanly callingget_api_version_spec. - Component Reusability Insights — Investigate generic shared definitions executing
list_domainsand fetch core parameters seamlessly viaget_domain_details. - Project & Lifecycle Control — Map team infrastructures inspecting groupings natively with
list_projectsand verify operational logic by callingget_project_details. - Ecosystem Verification — Audit backend dependencies natively invoking
list_api_integrationsto test GitHub, AWS, and GitLab sync parameters tied to your specs.
The SwaggerHub MCP Server exposes 10 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 SwaggerHub to OpenAI Agents SDK via MCP
Follow these steps to integrate the SwaggerHub 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 10 tools from SwaggerHub
Why Use OpenAI Agents SDK with the SwaggerHub MCP Server
OpenAI Agents SDK provides unique advantages when paired with SwaggerHub 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
SwaggerHub + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the SwaggerHub MCP Server delivers measurable value.
Automated workflows: build agents that query SwaggerHub, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries SwaggerHub, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through SwaggerHub tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query SwaggerHub to resolve tickets, look up records, and update statuses without human intervention
SwaggerHub MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect SwaggerHub to OpenAI Agents SDK via MCP:
get_api_details
Retrieves metadata for a SwaggerHub API definition
get_api_version_spec
Retrieves a specific version of a SwaggerHub API definition (OpenAPI spec)
get_domain_details
Retrieves metadata for a SwaggerHub domain
get_project_details
Retrieves details of a SwaggerHub project
list_api_integrations
Lists all CI/CD integrations configured for a SwaggerHub API
list_api_templates
Lists all available API templates on SwaggerHub
list_apis
List all API definitions owned by a SwaggerHub user or organization
list_domains
Lists all shared domains (reusable components) owned by a user or org
list_projects
Lists all projects in a SwaggerHub organization
search_apis
Search all public APIs on SwaggerHub by keyword
Example Prompts for SwaggerHub in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with SwaggerHub immediately.
"Search for public API specifications related to 'payment gateway' on SwaggerHub."
"List all active projects in our SwaggerHub organization."
"Ensure that the 'Acme-Billing' API has AWS API Gateway integration synced currently."
Troubleshooting SwaggerHub MCP Server with OpenAI Agents SDK
Common issues when connecting SwaggerHub to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
SwaggerHub + OpenAI Agents SDK FAQ
Common questions about integrating SwaggerHub 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 SwaggerHub 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 SwaggerHub to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.