Umami Cloud MCP Server for LlamaIndex 4 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Umami Cloud 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 MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Umami Cloud. "
"You have 4 tools available."
),
)
response = await agent.run(
"What tools are available in Umami Cloud?"
)
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 Umami Cloud MCP Server
The Umami Cloud MCP Server connects AI agents to the Umami Analytics API. It allows agents to retrieve real-time and historical website statistics, fetch pageviews, analyze active users, and export events dynamically while preserving end-user privacy.
LlamaIndex agents combine Umami Cloud tool responses with indexed documents for comprehensive, grounded answers. Connect 4 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.
The Umami Cloud MCP Server exposes 4 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.
How to Connect Umami Cloud to LlamaIndex via MCP
Follow these steps to integrate the Umami Cloud MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 4 tools from Umami Cloud
Why Use LlamaIndex with the Umami Cloud MCP Server
LlamaIndex provides unique advantages when paired with Umami Cloud through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Umami Cloud tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Umami Cloud tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Umami Cloud, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Umami Cloud tools were called, what data was returned, and how it influenced the final answer
Umami Cloud + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Umami Cloud MCP Server delivers measurable value.
Hybrid search: combine Umami Cloud real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Umami Cloud 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 Umami Cloud for fresh data
Analytical workflows: chain Umami Cloud queries with LlamaIndex's data connectors to build multi-source analytical reports
Umami Cloud MCP Tools for LlamaIndex (4)
These 4 tools become available when you connect Umami Cloud to LlamaIndex via MCP:
users
Get the number of active users on a website
websites.list
List websites configured in Umami
websites.metrics
Get specific metrics (urls, browsers, os, devices) for a website
websites.stats
Get summary statistics for a website in a time range
Example Prompts for Umami Cloud in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Umami Cloud immediately.
"Show me the top 5 pages by pageviews on my main website for the last 7 days."
"Analyze the bounce rate and absolute session duration from mobile users on the pricing page today."
"List the top 4 referral traffic sources matching 'social' for this month."
Troubleshooting Umami Cloud MCP Server with LlamaIndex
Common issues when connecting Umami Cloud to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpUmami Cloud + LlamaIndex FAQ
Common questions about integrating Umami Cloud MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Umami Cloud 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 Umami Cloud to LlamaIndex
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.