How to Use the GetStream MCP in OpenAI Agents SDK

Q: Does GetStream work with OpenAI Agents SDK guardrails?

Yes. Since the MCP Server exposes specific tools like batchfollow, the agent's built-in guardrails validate these actions before any API request leaves your environment.

Q: Can my OpenAI Agents SDK agent use GetStream for cross-user social features?

Absolutely. Use batchfollow and listfeedfollowers to let your agent manage complex social graphs, all while maintaining strict control over data access patterns.

Directly manage GetStream activity feeds and social graphs inside your OpenAI Agents SDK production pipeline.

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Connect GetStream MCP to OpenAI Agents SDK

Create your Vinkius account to connect GetStream 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 GetStream with OpenAI Agents SDK

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Full feed control for OpenAI Agents SDK

Your agent handles feed logic by calling `add_activity_to_feed` or `remove_activity_from_feed` directly. It automates the messy work of updating social timelines without writing custom middleware. This MCP Server exposes 23 endpoints that your agent uses to manipulate activities. It removes the need for manual API wrappers, letting the agent talk to your infrastructure.

Manage collections with OpenAI Agents SDK

Handle your data objects by using `batch_post_collections` or `update_collection_object`. Your agent reads and writes collection state during its task execution, keeping your data synchronized. Everything stays within your agent's execution flow. You verify state changes through the OpenAI dashboard, ensuring every record update happens as expected.

Media and file handling for OpenAI Agents SDK

Upload images and files directly using `upload_image` and `upload_file`. Your agent processes media assets automatically, triggering `process_image` to resize content before it hits your feed. Get Open Graph metadata with `get_open_graph` to enrich your activity payloads. This ensures your agent builds complete, ready-to-render posts for your users.

Setup guide

Set up GetStream 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 GetStream tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate GetStream 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="GetStream Agent",
            instructions="You have access to GetStream 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 GetStream MCP in OpenAI Agents SDK

You instantiate an MCPServerStreamableHttp object with your endpoint URL. Pass this instance into your Agent constructor's mcp_servers list to enable tool discovery.

Yes. Since the MCP Server exposes specific tools like `batch_follow`, the agent's built-in guardrails validate these actions before any API request leaves your environment.

Absolutely. Use `batch_follow` and `list_feed_followers` to let your agent manage complex social graphs, all while maintaining strict control over data access patterns.

It is. Set cacheToolsList to True to minimize overhead during runtime as the agent maps the 23 available endpoints.

The MCP Server operates in a sandboxed V8 isolate. It only touches activity metadata and collection objects, keeping your private user identifiers isolated from the agent's reasoning process.

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