Hotjar MCP Server for LlamaIndexGive LlamaIndex instant access to 15 tools to Check Hotjar Status, Get Feedback Widget, Get Heatmap, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Hotjar as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Hotjar app connector for LlamaIndex is a standout in the Customer Support category — giving your AI agent 15 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Hotjar. "
"You have 15 tools available."
),
)
response = await agent.run(
"What tools are available in Hotjar?"
)
print(response)
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 Hotjar MCP Server
Connect your Hotjar account to any AI agent and access user experience analytics through natural conversation.
LlamaIndex agents combine Hotjar tool responses with indexed documents for comprehensive, grounded answers. Connect 15 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Survey Management — List all surveys, inspect questions and settings, retrieve individual responses, and review aggregate statistics (completion rate, NPS score, trends)
- Feedback Widgets — Browse incoming feedback widgets, inspect rating breakdowns, and review individual user submissions with screenshots
- Heatmaps — List all heatmap snapshots and inspect click, scroll, and move data for specific pages
- Session Recordings — Browse session recordings with duration and page count, and inspect metadata and events for individual sessions
- Conversion Funnels — List all funnels with step-by-step drop-off data for conversion optimization
- User Lookup — Retrieve session history and behavior data for a specific user ID
- Site Management — List all tracked sites configured in your Hotjar account
The Hotjar MCP Server exposes 15 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 15 Hotjar tools available for LlamaIndex
When LlamaIndex connects to Hotjar through Vinkius, your AI agent gets direct access to every tool listed below — spanning heatmaps, session-recordings, user-feedback, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Verify connectivity
Get feedback widget details
Get heatmap details
Get recording details
Get survey details
Get survey statistics
List feedback widgets
List feedback responses
List funnels
List heatmaps
List recordings
List tracked sites
List survey responses
List surveys
Lookup user
Connect Hotjar to LlamaIndex via MCP
Follow these steps to wire Hotjar into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Hotjar MCP Server
LlamaIndex provides unique advantages when paired with Hotjar through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Hotjar tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Hotjar tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Hotjar, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Hotjar tools were called, what data was returned, and how it influenced the final answer
Hotjar + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Hotjar MCP Server delivers measurable value.
Hybrid search: combine Hotjar real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Hotjar to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Hotjar for fresh data
Analytical workflows: chain Hotjar queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Hotjar in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Hotjar immediately.
"Show the NPS survey results and the top feedback submissions this month."
"Show the heatmap data for our pricing page and the conversion funnel from landing to signup."
"Look up user behavior for user ID 'usr_12345' and show their session recordings."
Troubleshooting Hotjar MCP Server with LlamaIndex
Common issues when connecting Hotjar to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHotjar + LlamaIndex FAQ
Common questions about integrating Hotjar MCP Server with LlamaIndex.