How to Use the Substack MCP in OpenAI Agents SDK
Track and manage your Substack content lifecycle with the OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Substack MCP to OpenAI Agents SDK
Create your Vinkius account to connect Substack to OpenAI Agents SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.
Gemini
Key Capabilities
Monitor post performance data.
Your agent uses `get_post_stats` to pull key metrics on any piece of content. You get specific numbers like read counts and engagement rates, letting you know exactly which posts resonated. This makes it simple to compare the success of different articles or identify trends across your entire Substack publication.
Audit your subscriber base.
Need a list of who's subscribed? The `list_subscribers` tool fetches that data, giving you a clear roster. You can then process this list to segment users for targeted campaigns. This capability is great for running reports or feeding user lists into other parts of your production agent system.
Get full publication details.
The `get_publication_info` tool pulls core metadata about the Substack itself. This includes things like the publication's creation date and its general reach. It’s useful for agents that need to establish context before drafting a new post or running an analysis.
Set up Substack MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all Substack tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Substack tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Substack tools and returns structured results. Copy the full example on the right to get started.
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="Substack Agent",
instructions="You have access to Substack tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main())Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Substack. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about Substack MCP in OpenAI Agents SDK
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