Leadfeeder MCP Server for OpenAI Agents SDK 9 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Leadfeeder 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="Leadfeeder Assistant",
instructions=(
"You help users interact with Leadfeeder. "
"You have access to 9 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Leadfeeder"
)
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 Leadfeeder MCP Server
Connect your Leadfeeder tracking system to an AI agent to analyze high-quality B2B internet traffic. Track precise analytics without using heavy third-party dashboard setups directly in Cursor or Claude.
The OpenAI Agents SDK auto-discovers all 9 tools from Leadfeeder through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Leadfeeder, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- Discover Target Leads: Fetch the list of verified companies engaging with your tracking pixel on specific domains.
- Visitor Analytics: Drill into session specifics of organizations interacting behind the scenes.
- Sales Pipeline: Identify key B2B traffic and prioritize new cold email targets or warm follow-ups immediately.
The Leadfeeder MCP Server exposes 9 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 Leadfeeder to OpenAI Agents SDK via MCP
Follow these steps to integrate the Leadfeeder 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 9 tools from Leadfeeder
Why Use OpenAI Agents SDK with the Leadfeeder MCP Server
OpenAI Agents SDK provides unique advantages when paired with Leadfeeder 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
Leadfeeder + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Leadfeeder MCP Server delivers measurable value.
Automated workflows: build agents that query Leadfeeder, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Leadfeeder, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Leadfeeder tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Leadfeeder to resolve tickets, look up records, and update statuses without human intervention
Leadfeeder MCP Tools for OpenAI Agents SDK (9)
These 9 tools become available when you connect Leadfeeder to OpenAI Agents SDK via MCP:
get_account
Get details for a specific Leadfeeder account
get_custom_feed
Get details for a specific custom feed filter
get_lead
Get details for a specific lead
get_tracking_script
Get the tracking script for the account
list_account_visits
Get aggregate visits data across the entire account
list_accounts
Retrieve a list of accounts from Leadfeeder
list_custom_feeds
Retrieve the custom feeds active within a specific account
list_lead_visits
Get the website visits directly associated with a specific lead
list_leads
Retrieve a list of discovered leads within an account
Example Prompts for Leadfeeder in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Leadfeeder immediately.
"Analyze and list all identified corporate visitors targeting my site."
"Are there any manufacturing sector companies viewing our price points?"
"Highlight repeat prospects viewing documentation sections."
Troubleshooting Leadfeeder MCP Server with OpenAI Agents SDK
Common issues when connecting Leadfeeder to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Leadfeeder + OpenAI Agents SDK FAQ
Common questions about integrating Leadfeeder 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 Leadfeeder 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 Leadfeeder to OpenAI Agents SDK
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.