Plausible MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Plausible through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Plausible "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Plausible?"
)
print(result.data)
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.
Pydantic AI validates every Plausible tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
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 Pydantic AI 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 Pydantic AI via MCP
Follow these steps to integrate the Plausible MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
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 with type-safe schemas
Why Use Pydantic AI with the Plausible MCP Server
Pydantic AI provides unique advantages when paired with Plausible through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Plausible integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Plausible connection logic from agent behavior for testable, maintainable code
Plausible + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Plausible MCP Server delivers measurable value.
Type-safe data pipelines: query Plausible with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Plausible tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Plausible and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Plausible responses and write comprehensive agent tests
Plausible MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Plausible to Pydantic AI 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 Pydantic AI
Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI
Common issues when connecting Plausible to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiPlausible + Pydantic AI FAQ
Common questions about integrating Plausible MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
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 Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.