How to Use the COR MCP in OpenAI Agents SDK

Q: Can my OpenAI Agents SDK agent track COR tasks automatically?

Yes, your agent can call listcortasks whenever it needs an update. It maps task types through listcortasktypes to keep your reporting accurate.

Q: How do I filter project data in OpenAI Agents SDK?

Pass the project ID directly into listcortasks. This keeps your context window clean and focused on specific project pipelines.

Track agency margins and project hours directly inside your OpenAI Agents SDK agent system.

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Connect COR MCP to OpenAI Agents SDK

Create your Vinkius account to connect COR to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup COR with OpenAI Agents SDK

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Manage project lifecycles with OpenAI Agents SDK

Use `create_cor_project` to kick off new client work without leaving your agent loop. The server handles the heavy lifting of project setup while your agent maintains focus on the goal. Your agent can query `list_cor_projects` to see what needs attention. It keeps your data fresh by pulling project metadata directly from the source.

Monitor team output using OpenAI Agents SDK

Run `list_cor_tasks` to see what your team is currently grinding on. It filters by project ID, so your agent only sees the relevant technical pipelines. Use `list_cor_time_entries` to pull raw hours into your analysis. You get a clear picture of where the time went without manual spreadsheets.

Sync user data via OpenAI Agents SDK

Get clear visibility into your organization with `list_cor_teams` and `list_cor_team_members`. Your agent knows exactly who is available to pick up new work. Checking `get_cor_me` confirms the agent's current identity. It ensures your API calls hit the right account every single time.

Setup guide

Set up COR MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all COR tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives COR tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate COR tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="COR Agent",
            instructions="You have access to COR tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about COR MCP in OpenAI Agents SDK

Install the library and define your HTTP server parameters. Pass the server instance into your agent constructor to let it auto-discover every available tool.

Yes, your agent can call `list_cor_tasks` whenever it needs an update. It maps task types through `list_cor_task_types` to keep your reporting accurate.

It does. Since the SDK validates actions before they execute, your COR operations stay within the safety boundaries you define.

Pass the project ID directly into `list_cor_tasks`. This keeps your context window clean and focused on specific project pipelines.

Vinkius handles your connection through an ephemeral sandbox. Your agency project data and time entries stay encrypted in transit and are never logged by the Vinkius infrastructure.

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