Umami Analytics MCP Server
@MCP-Mirror
关于 Umami Analytics MCP Server
Mirror of
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"analytics_service": {
"command": "uv",
"args": [
"--directory",
"/path/to/analytics_service",
"run",
"analytics-service"
],
"env": {
"UMAMI_API_URL": "https://example.com",
"UMAMI_USERNAME": "yourUmamiUsername",
"UMAMI_PASSWORD": "yourUmamiPassword",
"UMAMI_TEAM_ID": "yourUmamiTeamId"
}
}
}
}工具
10Retrieve a list of websites and their IDs in your Umami account
Get key metrics like pageviews, visitors, bounce rate for a website
Analyze specific metrics like URLs, referrers, browsers, countries
Get time-series pageview data with customizable intervals
Monitor current number of active visitors on a website
Retrieve session IDs for specific events or time periods
Get detailed activity data for a specific session ID
Perform semantic search on many user journeys, returning the most relevant chunks for a given question
Capture visual snapshots of webpages
Retrieve and analyze webpage HTML source code
概览
What is Umami Analytics MCP Server?
A Model Context Protocol (MCP) server that enhances Claude with access to website analytics data from Umami. It enables Claude to analyze user behavior, track website performance, and generate data-driven insights.
How to use Umami Analytics MCP Server?
Install uv, then add the MCP server configuration to your Claude Desktop config file (claude_desktop_config.json) with the Umami API URL, username, password, and team ID. When you open Claude Desktop, the server connects automatically. Use the built-in "Create Dashboard Prompt" or interact via natural language; Claude will choose the appropriate tools.
Key features of Umami Analytics MCP Server
- Provides 10 analytical tools for Umami data.
- Offers semantic search on user journey chunks.
- Captures webpage screenshots and HTML via Crawl4AI.
- Supports custom prompt creation for repeatable workflows.
- Enables dashboard generation with guided prompts.
Use cases of Umami Analytics MCP Server
- Analyze user journeys and behavior patterns.
- Monitor real-time active visitors on a website.
- Generate performance dashboards and visualizations.
- Identify user pain points through semantic journey search.
- Improve site performance with contextual webpage context.
FAQ from Umami Analytics MCP Server
What are the prerequisites to run the server?
You need to install uv and have Umami account credentials: API URL, username, password, and team ID.
How do I configure the server in Claude Desktop?
Add a JSON entry under mcpServers in your claude_desktop_config.json, specifying uv as the command and the required environment variables (UMAMI_API_URL, UMAMI_USERNAME, UMAMI_PASSWORD, UMAMI_TEAM_ID).
Can I create my own prompts and workflows?
Yes, define a prompt structure in list_prompts() and implement its logic in get_prompt() within src/analytics_service/server.py.
How does the server handle large user journey data?
The get_docs tool chunks journey data, embeds them with a sentence transformer, and returns only the most relevant segments via semantic search, preventing context window overload.
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