alilxxey/openobserve-community-mcp

Overview

A community-built MCP server that connects AI assistants to OpenObserve, an observability platform. It enables querying logs, metrics, and traces through the Model Context Protocol. Written in Python, it is indexed from the awesome-mcp-servers list.

Best for

Best for
Developers using OpenObserve who want AI-assisted observability via MCP

Use cases

• Query OpenObserve logs and metrics via natural language
• Monitor system health and investigate incidents with AI assistance
• Integrate observability data into AI-driven workflows

How to use

Install

uvx --from openobserve-community-mcp openobserve-mcp init-config

Tools exposed

• list_streams
• get_stream_schema
• search_logs
• search_around
• search_values
• list_dashboards
• get_dashboard
• get_latest_traces

Notes

A community-built MCP server that connects AI assistants to OpenObserve, an observability platform. It enables querying logs, metrics, and traces through the Model Context Protocol. Written in Python, it is indexed from the awesome-mcp-servers list.

10 stars on GitHub. Last updated 2026-03-24. Licensed GPL-3.0.

Use cases

• Query OpenObserve logs and metrics via natural language
• Monitor system health and investigate incidents with AI assistance
• Integrate observability data into AI-driven workflows

Pros

• Open source and community-driven
• Python-based, easy to extend or modify
• Leverages MCP for standardized AI tool integration

Cons

• Low star count (10) suggests limited community adoption
• May lack comprehensive documentation or stability
• Dependent on OpenObserve instance availability and configuration

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.