ZenHub MCP Server for OpenAI Agents SDK 8 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect ZenHub 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="ZenHub Assistant",
instructions=(
"You help users interact with ZenHub. "
"You have access to 8 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from ZenHub"
)
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 ZenHub MCP Server
Connect your ZenHub account to any AI agent to streamline your agile project management on GitHub. This MCP server enables your agent to interact with pipelines, issues, estimates, and epics directly from natural language.
The OpenAI Agents SDK auto-discovers all 8 tools from ZenHub through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries ZenHub, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- Board Visibility — List all pipelines and issues for specific GitHub repositories or ZenHub workspaces
- Agile Status Management — Move issues between pipelines to update their workflow status instantly
- Precision Estimating — Set and retrieve story point estimates for any GitHub issue
- Epic Oversight — List and inspect ZenHub epics and their constituent issues
- Release Tracking — Access release reports and progress metadata for your projects
The ZenHub MCP Server exposes 8 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 ZenHub to OpenAI Agents SDK via MCP
Follow these steps to integrate the ZenHub 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 8 tools from ZenHub
Why Use OpenAI Agents SDK with the ZenHub MCP Server
OpenAI Agents SDK provides unique advantages when paired with ZenHub 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
ZenHub + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the ZenHub MCP Server delivers measurable value.
Automated workflows: build agents that query ZenHub, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries ZenHub, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through ZenHub tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query ZenHub to resolve tickets, look up records, and update statuses without human intervention
ZenHub MCP Tools for OpenAI Agents SDK (8)
These 8 tools become available when you connect ZenHub to OpenAI Agents SDK via MCP:
get_epic_data
Get details for a specific epic
get_repo_board
Get the ZenHub board for a repository
get_workspace_board
Get the ZenHub board for a specific workspace and repository
get_zenhub_issue_data
Get ZenHub-specific metadata for a GitHub issue
list_release_reports
List release reports for a repository
list_repo_epics
List all ZenHub epics for a repository
move_issue_between_pipelines
Move an issue to a different pipeline
set_issue_estimate
Set the story point estimate for an issue
Example Prompts for ZenHub in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with ZenHub immediately.
"Show me the ZenHub board for repository ID '12345678'."
"Move issue #45 in repo '12345678' to the 'In Progress' pipeline (ID: '56789') in workspace '98765'."
"What are the estimates for all issues in the current epic?"
Troubleshooting ZenHub MCP Server with OpenAI Agents SDK
Common issues when connecting ZenHub to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
ZenHub + OpenAI Agents SDK FAQ
Common questions about integrating ZenHub 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 ZenHub 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 ZenHub to OpenAI Agents SDK
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.