[
https://issues.apache.org/jira/browse/GSOC-293?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Maxim Solodovnik updated GSOC-293:
----------------------------------
Labels: HertzBeat agent gsoc gsoc2025 mcp (was: agent gsoc gsoc2025
hertzbeat mcp)
> [GSOC][HertzBeat] AI Agent Based on the MCP Protocol for Monitoring Info
> Interaction
> ------------------------------------------------------------------------------------
>
> Key: GSOC-293
> URL: https://issues.apache.org/jira/browse/GSOC-293
> Project: Comdev GSOC
> Issue Type: Task
> Reporter: Chao Gong
> Priority: Major
> Labels: HertzBeat, agent, gsoc, gsoc2025, mcp
>
> Website: https://hertzbeat.apache.org/
> Github: http://github.com/apache/hertzbeat/
> **Background**
> Apache HertzBeat is an open-source real-time monitoring tool that supports a
> wide range of monitoring targets, including web services, databases,
> middleware, and more. It features high performance, scalability, and security.
> With the advancement of artificial intelligence (AI) technologies,
> integrating AI with monitoring systems can significantly enhance their
> usability and interactivity. By developing an AI Agent based on the Model
> Context Protocol (MCP), we aim to enable conversational interaction for
> querying monitoring information, adding new monitoring tasks, and retrieving
> monitoring metrics. This will provide a more user-friendly and intelligent
> monitoring management experience.
> **Objectives**
> 1. Research and Implementation: Develop an AI Agent based on Apache HertzBeat
> and the MCP protocol to enable conversational interaction with users.
> 2. Functional Implementation:
> - Query Monitoring And Alarm Information: Allow users to query the status of
> monitoring targets (e.g., normal, abnormal) and retrieve metrics data (e.g.,
> CPU usage, memory usage, response time), alarm data through conversational
> commands.
> - Add New Monitoring Tasks: Enable users to add new monitoring targets (e.g.,
> web services, databases, middleware) and configure alert thresholds via
> conversational commands.
> - Retrieve Monitoring Metrics Data: Allow users to obtain metrics data for
> specific monitoring targets and support data visualization via conversational
> commands.
> **Requirements Analysis**
> - Apache HertzBeat: As the core backend for the monitoring system, it
> provides functions for data collection, storage, and management.
> - MCP Protocol: An open protocol that enables seamless integration between
> LLM applications and external data sources and tools.
> - Front-end Interaction: Develop a user-friendly interface that supports
> voice or text input and displays monitoring information and interaction
> results.
> **Recommended Skills**
> - Java + TypeScript: Apache HertzBeat is developed based on this technology
> stack. Therefore, mastering these technologies is crucial for integrating
> with HertzBeat.
> - SpringAi: It is recommended to use SpringAi to build the AI agent.
> - LLM + MCP: You need to have an understanding of LLM (Large Language Models)
> and the MCP protocol. SpringAi seem supports the MCP protocol or consider use
> the mcp-sdk directly.
> **Size**
> - Difficulty: Hard
> - Project size: ~350 hours
> **Potential Mentors**
> - Chao Gong: gongc...@apache.org
>
> - Shenghang Zhang: shengh...@apache.org
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
---------------------------------------------------------------------
To unsubscribe, e-mail: gsoc-unsubscr...@community.apache.org
For additional commands, e-mail: gsoc-h...@community.apache.org
