Grafana Mcp Analyzer

by SailingCoder

MCP Client
  • other

让AI助手直接分析你的Grafana监控数据 - A Model Context Protocol server for Grafana data analysis

About

What is Grafana Mcp Analyzer?

Grafana Mcp Analyzer is an MCP server library that enables AI assistants like Claude and ChatGPT to directly understand and analyze Grafana monitoring data through natural language conversation.

How to use Grafana Mcp Analyzer?

Key features of Grafana Mcp Analyzer

- Natural conversational query of monitoring data
- Intelligent anomaly detection in metrics
- Supports Prometheus, MySQL, Elasticsearch data sources
- Provides optimization suggestions beyond raw data
- Small package size of only 52 KB

Use cases of Grafana Mcp Analyzer

- Ask AI about server health and receive immediate analysis (e.g., CPU usage)
- Automatically detect anomalies in monitoring data without manual chart review
- Get actionable optimization suggestions from Grafana metrics

FAQ from Grafana Mcp Analyzer

Which AI assistants does it work with?

It works with Claude, ChatGPT, and other AI assistants that support the MCP protocol.

What data sources are supported?

It supports Grafana data sources such as Prometheus, MySQL, and Elasticsearch.

How large is the package?

The package is only 52 KB.

Does it just fetch data or also analyze it?

It both retrieves monitoring data and provides intelligent analysis, anomaly identification, and specific optimization recommendations.

Is there a pricing or licensing model?

The README does not mention pricing or licensing details.

Details

Author
SailingCoder
Category
other
Repository
sailingcoder/grafana-mcp-analyzer

让AI直接理解你的监控数据,智能分析运维状况

想象一下这样的场景:

您问AI:"我的服务器现在怎么样?"
AI直接查看您的Grafana监控,回答:"CPU使用率偏高,建议检查这几个进程..."
不用再盯着复杂的监控图表,AI帮您分析一切!

Grafana MCP Analyzer 是一个基于 MCP (Model Context Protocol) 的服务器库,让Claude、ChatGPT等AI助手能够:

💬 自然对话式查询:"帮我看看内存使用情况" → AI立即分析并给出建议
🔍 智能异常识别:AI主动发现并告知监控数据中的异常
📊 多数据源支持:支持Prometheus、MySQL、Elasticsearch等各种Grafana数据源
💡 智能建议:不仅能展示监控数据,还能提供具体的优化建议
🚀 效率提升:无需手动分析图表,AI直接解读Grafana数据并给出分析结论
💡 体积小:包的体积很小,只有52KB