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Plausible Model Context Protocol Server

by AVIMBU

A Model Context Protocol (MCP) server implementation for interacting with the Plausible Analytics API. This server allows AI models to query analytics data from Plausible.

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What is Plausible Model Context Protocol Server?

This is a Model Context Protocol (MCP) server that enables AI models to access and query analytics data from Plausible Analytics. It acts as an intermediary, allowing AI to request and receive relevant analytics information.

How to use Plausible Model Context Protocol Server?

To use this server, configure it within your Claude Desktop MCP Server config file by specifying the command, arguments (pointing to the server's entry point), and environment variables (PLAUSIBLE_API_URL and PLAUSIBLE_API_KEY). Then, you can interact with it using prompts like 'Can you provide a daily overview of my analytics for avimbu.com?'

Key features of Plausible Model Context Protocol Server

  • Connects AI models to Plausible Analytics

  • Enables querying of analytics data

  • Provides a structured interface for data access

  • Supports local development and testing

Use cases of Plausible Model Context Protocol Server

  • Generating analytics reports using AI

  • Providing AI-powered insights from Plausible data

  • Automating analytics data retrieval for AI applications

  • Integrating Plausible analytics into AI workflows

FAQ from Plausible Model Context Protocol Server

What is the purpose of this server?

It allows AI models to query analytics data from Plausible Analytics.

How do I run this server locally?

Configure it in your Claude Desktop MCP Server config file and run node dist/index.js after building the project.

What environment variables are required?

PLAUSIBLE_API_URL and PLAUSIBLE_API_KEY are required.

Can I use this with other AI models besides Claude?

While the documentation focuses on Claude, the MCP server architecture should allow integration with other AI models that support MCP.

Where can I get support?

You can contact AVIMBU via their website.