MCP Observability
MCP server for querying logs from observability platforms with unified search and tracing
What is MCP Observability?
MCP Observability is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to mcp server for querying logs from observability platforms with unified search and tracing
MCP server for querying logs from observability platforms with unified search and tracing
This server falls under the Monitoring & Observability category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- MCP server for querying logs from observability platforms wi
Use Cases
Maintainer
Works with
Installation
PIP
pip install mcp-observability-serverManual Installation
pip install mcp-observability-serverConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
Frequently Asked Questions about MCP Observability
What is MCP Observability?
MCP Observability is a Model Context Protocol (MCP) server that mcp server for querying logs from observability platforms with unified search and tracing It connects AI assistants to external tools and data sources through a standardized interface.
How do I install MCP Observability?
Install via pip with: pip install mcp-observability-server. Then configure your AI client to connect to this MCP server.
Which AI clients work with MCP Observability?
MCP Observability works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is MCP Observability free to use?
Yes, MCP Observability is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
MCP Observability Alternatives — Similar Monitoring & Observability Servers
Looking for alternatives to MCP Observability? Here are other popular monitoring & observability servers you can use with Claude, Cursor, and VS Code.
Netdata
★ 78.9kReal-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Kubeshark
★ 11.9keBPF-powered network observability for Kubernetes. Indexes L4/L7 traffic with full K8s context, decrypts TLS without keys. Queryable by AI agents via MCP and humans via dashboard.
Mission Control
★ 4.9kSelf-hosted AI agent orchestration platform: dispatch tasks, run multi-agent workflows, monitor spend, and govern operations from one mission control dashboard.
Grafana
★ 3.0kThis MCP server enables natural-language querying of Grafana logs by automatically detecting log sources and service labels. It provides read-only access to log data with intelligent caching for efficient repeat queries.
Sentrux
★ 2.4kReal-time architectural sensor that helps AI agents close the feedback loop, enabling recursive self-improvement of code quality. Pure Rust.
OpenInference
★ 986OpenTelemetry Instrumentation for AI Observability
Browse More Monitoring & Observability MCP Servers
Explore all monitoring & observability servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.
Set Up MCP Observability in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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