How to Use the Leadfeeder MCP in OpenAI Agents SDK
Feed real-time Leadfeeder visitor intent straight to your OpenAI Agents SDK pipelines to trigger instant sales handoffs.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Leadfeeder MCP to OpenAI Agents SDK
Create your Vinkius account to connect Leadfeeder 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.
Filter hot Leadfeeder prospects with OpenAI Agents SDK
Your OpenAI Agents SDK pipeline can run `list_leads` to pull active Leadfeeder companies directly into your python agent's context window. It's easy for your OpenAI agent to instantly check if a high-value Leadfeeder account is browsing your site before calling `get_lead` for firmographic details. By setting up specialized OpenAI Agents SDK guardrails, you ensure the agent only triggers notifications when Leadfeeder accounts match your ideal customer profile. The OpenAI Agents SDK handles the routing, passing Leadfeeder profiles to your sales reps before the visitor even closes the tab.
Map Leadfeeder journeys using this MCP Server
This MCP Server enables your OpenAI Agents SDK setup to dig into specific user behavior by calling `list_lead_visits` to check which pages a Leadfeeder lead viewed. It maps the entire session history directly into your OpenAI agent's memory to ensure your Leadfeeder outreach is highly contextual. Using `get_custom_feed`, your OpenAI agents can filter out random web traffic and focus strictly on Leadfeeder custom feeds. This keeps your OpenAI Agents SDK pipeline clean and guarantees your sales team receives highly qualified Leadfeeder alerts.
Audit Leadfeeder tracking via OpenAI Agents SDK
Your OpenAI Agents SDK pipeline can verify if your Leadfeeder tracking script is active by calling `get_tracking_script` directly from your script. This allows the OpenAI agent to confirm that Leadfeeder is actively recording web traffic before running outbound sales plays. If the Leadfeeder script is missing, you'll see the OpenAI agent flag the error instantly within your python console. This prevents your OpenAI Agents SDK workflows from running on empty Leadfeeder databases.
Set up Leadfeeder 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 Leadfeeder tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Leadfeeder tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Leadfeeder 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="Leadfeeder Agent",
instructions="You have access to Leadfeeder 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 Leadfeeder. 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.
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Common questions about Leadfeeder MCP in OpenAI Agents SDK
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