Matomo MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Matomo 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 Matomo. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Matomo?"
)
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 Matomo MCP Server
Connect your Matomo analytics instance to any AI agent and gain deep insights into your website traffic through natural conversation.
LlamaIndex agents combine Matomo tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Visits Summary — Get aggregated metrics on visits, actions, and bounce rates
- Real-time Monitoring — See the latest visitor details and actions as they happen
- Top Content — Identify your most visited pages, referring websites, and social networks
- Visitor Profiles — Inspect complete history and behavior for specific visitor IDs
- Goal Tracking — List and monitor conversion goals configured in your instance
The Matomo MCP Server exposes 10 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 Matomo to LlamaIndex via MCP
Follow these steps to integrate the Matomo 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 10 tools from Matomo
Why Use LlamaIndex with the Matomo MCP Server
LlamaIndex provides unique advantages when paired with Matomo through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Matomo tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Matomo tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Matomo, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Matomo tools were called, what data was returned, and how it influenced the final answer
Matomo + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Matomo MCP Server delivers measurable value.
Hybrid search: combine Matomo real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Matomo 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 Matomo for fresh data
Analytical workflows: chain Matomo queries with LlamaIndex's data connectors to build multi-source analytical reports
Matomo MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Matomo to LlamaIndex via MCP:
get_goals
Get the list of goals
get_live_last_visits
Get last visits in real-time
get_site_details
Get details for a specific website
get_top_pages
Get the most visited pages
get_top_referrers
Get the top referrer types
get_top_socials
Get the top referring social networks
get_top_websites
Get the top referring websites
get_visitor_profile
Get a detailed profile for a visitor
get_visits_summary
Get a summary of visits
list_sites
List all websites in Matomo
Example Prompts for Matomo in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Matomo immediately.
"Show me a summary of visits for today."
"What are the top pages on my site this week?"
"List all sites configured in Matomo."
Troubleshooting Matomo MCP Server with LlamaIndex
Common issues when connecting Matomo to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMatomo + LlamaIndex FAQ
Common questions about integrating Matomo 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 Matomo 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 Matomo to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.