How to Use the Hotjar (Behavior Analytics) MCP in AutoGen

Q: Can multiple AutoGen agents use this Hotjar (Behavior Analytics) MCP Server at the same time?

Yes, all agents in your group chat can access tools like listrecordings or listfeedback. They can share these results in their conversation history to debate the best fix.

Let your AutoGen agents debate user behavior patterns using live Hotjar data to reach consensus on UI fixes.

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Connect Hotjar (Behavior Analytics) MCP to AutoGen

Create your Vinkius account to connect Hotjar (Behavior Analytics) to AutoGen 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 Hotjar (Behavior Analytics) with AutoGen

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Consensus-driven UX debugging with AutoGen

You can set up an AutoGen multi-agent debate where one agent analyzes quantitative drop-offs using Hotjar's `list_funnels` and another reviews qualitative feedback via `list_feedback`. This MCP Server gives both AutoGen agents the raw Hotjar data they need to negotiate a solution. Instead of relying on a single agent's guess, the AutoGen team debates why users are leaving based on Hotjar sessions. They only output a recommendation once they agree on the root cause of the Hotjar funnel drop-off.

Resolve design disputes with heatmap evidence

When your AutoGen product agent wants to move a button, your UX agent can challenge the decision using actual Hotjar data. The UX agent calls `get_heatmap` and `list_heatmaps` to show exactly where users are clicking. The AutoGen agents analyze the Hotjar coordinate density to prove whether the current button is actually getting ignored. This keeps your automated design decisions grounded in Hotjar behavioral facts, not AutoGen agent assumptions.

Automated survey analysis via agent collaboration

You can deploy an AutoGen agent team where one agent fetches active campaigns using Hotjar's `list_surveys` and another extracts the raw answers via `list_survey_responses`. A third AutoGen analyst agent then reviews the Hotjar findings. The AutoGen agents collaborate to sort the Hotjar responses, flagging urgent bugs for immediate attention. This team dynamic ensures that raw Hotjar text feedback is thoroughly vetted by AutoGen before any alerts are sent.

Setup guide

Set up Hotjar (Behavior Analytics) MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Hotjar (Behavior Analytics) tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Hotjar (Behavior Analytics)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Hotjar (Behavior Analytics) data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Hotjar (Behavior Analytics)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Hotjar (Behavior Analytics) data")
    print(result.messages[-1].content)

Get your connection token →

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Common questions about Hotjar (Behavior Analytics) MCP in AutoGen

Use the MCP tool adapter to convert the server schema. Pass the resulting tools list to your `AssistantAgent` constructor so they can call endpoints like `list_sites` or `get_site`.

Yes, all agents in your group chat can access tools like `list_recordings` or `list_feedback`. They can share these results in their conversation history to debate the best fix.

The Vinkius MCP infrastructure manages the connection and helps buffer calls. If your agents spam `get_survey` during a debate, the underlying server handles the queue to prevent API lockouts.

Yes, the framework allows the agent to select the appropriate tool based on the conversation flow. If a teammate agent asks about drop-offs, the analyst agent will call `list_funnels` automatically.

Token authentication for this MCP Server is handled securely via the Vinkius platform. Your API credentials are encrypted and never exposed to the AutoGen agents or stored in the chat logs.

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