How to Use the Fathom Analytics MCP in OpenAI Agents SDK

Q: How do I connect the Fathom Analytics MCP server to my OpenAI Agents SDK project?

Install the package using pip install openai-agents and initialize MCPServerStreamableHttp with your Vinkius connection URL. Pass this server object into your Agent constructor using the mcpservers parameter to enable automatic tool discovery.

Q: Does the OpenAI Agents SDK support real-time Fathom Analytics tracking?

Yes. Your agent uses getcurrentvisitors to monitor concurrent users instantly. It can also query getpageviews to track long-term traffic trends.

Q: How do I optimize tool discovery performance in OpenAI Agents SDK?

Set cacheToolsList=True in your SDK configuration. This stops the agent from refetching the tool definitions on every single run, keeping your Fathom Analytics query loops fast.

Track clean, cookieless traffic trends and monitor live visitors directly within your OpenAI Agents SDK production pipelines.

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Connect Fathom Analytics MCP to OpenAI Agents SDK

Create your Vinkius account to connect Fathom Analytics 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 Fathom Analytics with OpenAI Agents SDK

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Audit live traffic with this Fathom Analytics MCP Server

This Fathom Analytics MCP Server gives your OpenAI agents direct access to live visitor metrics using `get_current_visitors` to monitor traffic spikes as they happen. Your OpenAI agent calls this tool to check concurrent users, allowing the SDK to trigger Slack alerts or scale resources during unexpected load. By integrating this analytical server with your OpenAI Agents SDK setup, you bypass complex API wrapper maintenance. The OpenAI agent reads live Fathom site data directly, making real-time operational decisions based on actual traffic volume without manual human monitoring.

Analyze conversion milestones with OpenAI Agents SDK

The `get_event` tool pulls exact completion numbers for custom goals, letting your OpenAI agent evaluate marketing campaigns on the fly. Your agent uses `list_events` to identify active conversion tags and matches them against Fathom traffic sources to determine which channels drive actual signups. The OpenAI Agents SDK manages these Fathom tool calls with built-in guardrails, verifying the agent only requests event data for authorized site IDs. This prevents unauthorized data access while allowing autonomous OpenAI agents to generate daily performance reports.

Map referrer and device trends

The `get_referrers` tool exposes where your visitors come from, while `get_device_stats` breaks down whether they browse on mobile, tablet, or desktop. Your OpenAI agent queries these Fathom tools to build a clear picture of user acquisition without dealing with messy raw logs. Because the OpenAI Agents SDK supports direct handoffs between specialized agents, one agent can fetch the Fathom referrer breakdown while another optimizes ad spend based on those metrics. This modular MCP architecture keeps your data pipelines fast and isolated.

Setup guide

Set up Fathom Analytics 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 Fathom Analytics tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Fathom Analytics 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="Fathom Analytics Agent",
            instructions="You have access to Fathom Analytics tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Fathom Analytics. 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 Fathom Analytics MCP in OpenAI Agents SDK

Install the package using `pip install openai-agents` and initialize `MCPServerStreamableHttp` with your Vinkius connection URL. Pass this server object into your Agent constructor using the `mcp_servers` parameter to enable automatic tool discovery.

Yes. Your agent uses `get_current_visitors` to monitor concurrent users instantly. It can also query `get_pageviews` to track long-term traffic trends.

The SDK uses built-in guardrails to validate tool arguments before execution. If your agent attempts to query a site ID that you haven't authorized, the SDK blocks the call before it hits the Fathom Analytics API.

Set `cacheToolsList=True` in your SDK configuration. This stops the agent from refetching the tool definitions on every single run, keeping your Fathom Analytics query loops fast.

This server only accesses aggregate pageviews, custom event counts, and device statistics, completely ignoring personal data like IP addresses. Vinkius runs the server in an isolated V8 sandbox, ensuring your API token never leaks to the LLM or external networks.

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