Conduit 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 Conduit 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="Conduit Assistant",
instructions=(
"You help users interact with Conduit. "
"You have access to 8 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Conduit"
)
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 Conduit MCP Server
Connect your AI agent seamlessly with Conduit, the modern data integration and synchronization platform. Utilizing natural language interactions, users can instruct the AI to oversee active streaming health, check connectors, and extract pipeline logs without accessing the conventional web dashboard interfaces.
The OpenAI Agents SDK auto-discovers all 8 tools from Conduit through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Conduit, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- Pipeline Management — Request status overviews of active, paused, or degraded data integration pipelines efficiently.
- Connector Auditing — Ask the agent to locate specific connectors (source or destination) mapped to your critical infrastructure.
- Log Evaluation — Fetch recent application logs or streaming output reports via conversation to debug integration errors on the fly.
The Conduit 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 Conduit to OpenAI Agents SDK via MCP
Follow these steps to integrate the Conduit 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 Conduit
Why Use OpenAI Agents SDK with the Conduit MCP Server
OpenAI Agents SDK provides unique advantages when paired with Conduit 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
Conduit + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Conduit MCP Server delivers measurable value.
Automated workflows: build agents that query Conduit, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Conduit, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Conduit tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Conduit to resolve tickets, look up records, and update statuses without human intervention
Conduit MCP Tools for OpenAI Agents SDK (8)
These 8 tools become available when you connect Conduit to OpenAI Agents SDK via MCP:
get_run_status
Returns detailed status, timing, and error information. Retrieve the current status of a specific workflow run
get_workflow
Returns source, destination, and current status. Retrieve detailed information about a specific workflow
list_available_destinations
Retrieve available data destination connector types supported by Conduit
list_available_sources
Retrieve available data source connector types supported by Conduit
list_connections
Retrieve a list of all active source and destination connections
list_workflow_runs
Returns the execution history with status and timestamps for each run. Retrieve the history of runs for a specific workflow
list_workflows
Use this as a starting point to discover workflow IDs for subsequent operations. Retrieve a list of all data integration workflows in Conduit
trigger_workflow
Use list_workflows first to find the workflow ID. Manually trigger a run for a specific workflow
Example Prompts for Conduit in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Conduit immediately.
"Retrieve the current status of all major pipelines running in the production Conduit instance."
"Check if there's a configured destination connector named 's3-analytics-bucket' and briefly describe its configuration parameters."
"Pause the pipeline 'MySQL-to-Kafka' immediately."
Troubleshooting Conduit MCP Server with OpenAI Agents SDK
Common issues when connecting Conduit to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Conduit + OpenAI Agents SDK FAQ
Common questions about integrating Conduit 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 Conduit 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 Conduit to OpenAI Agents SDK
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.