"How to Embed MCP into a Django Application" matching MCP servers:

Enables AI assistants to monitor and troubleshoot AWS Application Signals services by tracking service health, analyzing SLO compliance, querying CloudWatch metrics, and investigating issues using distributed tracing with AWS X-Ray.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

The policy enforcement plane for MCP: deterministic admission and egress policy, attributable audit, and SIEM export for your MCP server fleet. Self-hosted and MIT licensed.

MCP server that exposes Avangenio's service status by fetching and parsing status.avangenio.com/data.txt into normalized JSON.

BeamScope gives AI coding agents access to your running BEAM application through a resilient TCP architecture that survives app restarts.

Enables AI assistants to search, analyze, and debug application API traffic captured by Tusk Drift, including HTTP requests, database queries, distributed traces, latency metrics, and error rates.

A read-only MCP server for Proxmox VE that provides AI assistants with structured visibility into cluster nodes, guests, storage, and Docker workloads. It is designed to prevent any mutating operations by construction.

An MCP server that decodes V8 CPU profiles into token-efficient bottleneck summaries for AI agents, enabling them to analyze CPU consumption, call trees, GC pressure, and async bottlenecks.

Provides tools for accessing Alibaba Cloud observability products including SLS (Log Service) and ARMS (Application Real-time Monitoring Service), allowing any MCP-compatible AI assistants to quickly interact with these services.

MCP server for inspecting IBM Liberty/WebSphere application servers over SSH, enabling reading sanitized configs, performing health checks, and searching logs remotely.

An MCP server that enables AI agents to safely operate multi-cluster Kubernetes fleets through an Open Cluster Management hub, with policy enforcement, human approval, and audit tracing.

Enables AI agents to analyze ROS2 log files across multiple nodes by merging them into a unified timeline and providing smart query tools, without requiring ROS2 installation.

An MCP server that connects AI agents to Scouter APM, enabling natural-language queries against real-time application performance data.

Enables AI agents to access New Relic logs and APM data through the NerdGraph API. It allows users to execute NRQL queries, retrieve application performance metrics, and analyze transaction traces using natural language.

Provides read-only observability and operational insight into a MuleSoft Anypoint Platform estate, enabling natural-language queries for application logs, archived log search, Runtime Manager inventory, API Manager instances, and Exchange assets using your own credentials.

MCP server for log file analysis. Gives LLMs the ability to efficiently analyze large log files without loading them into context.

Enables LLMs to query telemetry data via the Spyglass AI agent, providing intelligent insights about application performance, errors, and bottlenecks.