How to Use the Microsoft Clarity MCP in AutoGen

Q: Can an AutoGen agent debate session recordings from Microsoft Clarity?

Yes, one agent can retrieve session details using getrecording while a critic agent challenges the interpretation. They collaborate to find the exact moment a user abandoned a checkout flow.

Let your AutoGen agents debate UI fixes using live Microsoft Clarity behavior data.

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Connect Microsoft Clarity MCP to AutoGen

Create your Vinkius account to connect Microsoft Clarity 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 Microsoft Clarity with AutoGen

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Let AutoGen agents debate rage click fixes

The `list_rage_clicks` tool provides the exact coordinates and pages where users lost their patience. In an AutoGen setup, one agent can pull this list while another proposes layout changes. They debate the root cause of the frustration in a structured conversation. This consensus-driven approach ensures you only deploy fixes that address actual user pain.

Audit site performance with this MCP Server

The `get_live_insights` tool delivers real-time telemetry on active sessions and anomalies. Your monitoring agent checks this tool periodically and alerts a developer agent if metrics spike. The developer agent then requests details from `list_dead_clicks` to isolate the bug. This multi-agent loop automates the entire first line of UX defense.

Analyze user navigation via multi-agent conversations

The `list_top_pages` tool retrieves your most visited URLs to prioritize optimization work. Your planning agent uses this list to direct the focus of your design audit agents. Instead of guessing where to start, the agents look at the traffic data first. They then pull heatmaps for only the highest-traffic pages to maximize your design ROI.

Setup guide

Set up Microsoft Clarity 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 Microsoft Clarity 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="Microsoft Clarity_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Microsoft Clarity data")
print(result.messages[-1].content)

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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="Microsoft Clarity_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Microsoft Clarity data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Microsoft Clarity. 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 Microsoft Clarity MCP in AutoGen

You pass the tool list from the adapter to your AssistantAgent constructor. This exposes tools like `get_dashboard` directly to the conversational agent loop.

Yes, one agent can retrieve session details using `get_recording` while a critic agent challenges the interpretation. They collaborate to find the exact moment a user abandoned a checkout flow.

The MCP tool adapter handles all schema conversions automatically under the hood. You don't have to manually format inputs for tools like `get_scroll_depth`.

Yes, AutoGen supports stdio transport, allowing you to run your conversational UX audit agents directly from your terminal or CI/CD pipelines.

The MCP Server connects using single-token authentication managed by Vinkius, and all project queries via `get_project` run inside sandboxed isolates. No raw API keys or behavioral recordings are ever exposed to the agent conversation log.

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