Plausible 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 Plausible as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 Plausible. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Plausible?"
)
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 Plausible MCP Server
Connect your Plausible Analytics account to any AI agent and take full control of your website performance metrics through natural conversation.
LlamaIndex agents combine Plausible 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
- Real-time Insights — Get the current number of active visitors on your site.
- Aggregate Performance — Retrieve total visitors, pageviews, bounce rates, and visit durations for any period (30d, 7d, today).
- Growth Tracking — Fetch timeseries data to understand your traffic trends over time.
- Audience Breakdown — Analyze your visitors by top sources, pages, countries, devices, browsers, and operating systems.
- Custom Property Analysis — Break down stats by any custom property supported by the Plausible API.
The Plausible 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 Plausible to LlamaIndex via MCP
Follow these steps to integrate the Plausible 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 Plausible
Why Use LlamaIndex with the Plausible MCP Server
LlamaIndex provides unique advantages when paired with Plausible through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Plausible tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Plausible tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Plausible, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Plausible tools were called, what data was returned, and how it influenced the final answer
Plausible + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Plausible MCP Server delivers measurable value.
Hybrid search: combine Plausible real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Plausible 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 Plausible for fresh data
Analytical workflows: chain Plausible queries with LlamaIndex's data connectors to build multi-source analytical reports
Plausible MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Plausible to LlamaIndex via MCP:
get_aggregate_stats
, for a period (e.g., "30d", "7d", "day"). Get aggregate site statistics
get_custom_breakdown
g., "visit:source", "event:page"). Get breakdown by custom property
get_realtime_visitors
Get current active visitors
get_timeseries_stats
Get site stats over time
get_top_browsers
Get visitors by browser
get_top_countries
Get visitors by country
get_top_devices
Get visitors by device type
get_top_os
Get visitors by operating system
get_top_pages
Get most visited pages
get_top_sources
Get top traffic sources
Example Prompts for Plausible in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Plausible immediately.
"How many visitors are on my site right now?"
"Show me the top 5 pages by traffic for the last 7 days."
"What was my bounce rate for the last 30 days?"
Troubleshooting Plausible MCP Server with LlamaIndex
Common issues when connecting Plausible to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPlausible + LlamaIndex FAQ
Common questions about integrating Plausible 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 Plausible 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 Plausible to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.